The Average IQ in Ukraine is 94.95 - how do you compare?

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.

Cronbach's alpha

Cronbach's alpha is a measure of internal consistency reliability, which means it assesses how consistently the items in a test measure a single underlying construct (in this case, IQ).

Our test currently has a global Cronbach's alpha of α=0.83 among all the people who have taken our test. Here is a commonly used rating scale for interpreting Cronbach's alpha values:

0.9 ≤ α: Excellent internal consistency
0.8 ≤ α < 0.9: Good internal consistency
0.7 ≤ α < 0.8: Acceptable internal consistency
0.6 ≤ α < 0.7: Questionable internal consistency
0.5 ≤ α < 0.6: Poor internal consistency
α < 0.5: Unacceptable internal consistency


A high Cronbach's alpha coefficient value suggests that the items in the IQ test are highly correlated with each other, indicating that they are measuring the same underlying construct (i.e., intelligence). This indicates that the test is reliable and consistent in measuring IQ.

In contrast, a low Cronbach's alpha coefficient value suggests that the items in the IQ test are not highly correlated with each other, indicating that they may not be measuring the same underlying construct (i.e., intelligence) in a consistent way. This suggests that the test may not be reliable or consistent in measuring IQ.

Therefore, Cronbach's alpha can be used as an indicator of the overall reliability and consistency of an IQ test, and it can be useful for evaluating the quality of the test and the validity of the scores.

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion in a set of data. For IQ test results that form a Gaussian curve, the standard deviation can provide important information about the distribution of scores.

For IQ tests, the standard deviation is often set at 15 points. This means that approximately 68% of the test-takers will score within 15 points of the mean, 95% will score within 30 points of the mean, and 99.7% will score within 45 points of the mean.

The standard deviation of an IQ test score distribution can vary between countries. A tighter (i.e., smaller) standard deviation means that the scores are more closely clustered around the mean, while a wider (i.e., larger) standard deviation means that the scores are more spread out.

For example, let's say we have two countries, A and B, that have the same mean IQ score of 100 but different standard deviations. In country A, the standard deviation is 10, while in country B, the standard deviation is 20. This means that the scores in country A are more tightly clustered around the mean, while the scores in country B are more spread out.

In terms of interpretation, a smaller standard deviation indicates that the population has less variability in IQ scores, meaning that there is less diversity in cognitive abilities within the population. On the other hand, a larger standard deviation indicates greater variability in IQ scores, which suggests a wider range of cognitive abilities within the population.

However, it is important to note that the standard deviation is just one aspect of the distribution of IQ scores, and should be interpreted in conjunction with other statistics such as the mean and percentiles. Additionally, it is important to avoid making generalizations or stereotyping based on IQ scores or other measures of cognitive ability, as these can be influenced by a wide range of factors beyond an individual's control.