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In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related uses: * It can be used to describe the difference between two proportions as "small", "medium", or "large". * It can be used to determine if the difference between two proportions is "meaningful". * It can be used in calculating the sample size for a future study.

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  • In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related uses: * It can be used to describe the difference between two proportions as "small", "medium", or "large". * It can be used to determine if the difference between two proportions is "meaningful". * It can be used in calculating the sample size for a future study.
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  • In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related uses: * It can be used to describe the difference between two proportions as "small", "medium", or "large". * It can be used to determine if the difference between two proportions is "meaningful". * It can be used in calculating the sample size for a future study. When measuring differences between proportions, Cohen's h can be used in conjunction with hypothesis testing. A "statistically significant" difference between two proportions is understood to mean that, given the data, it is likely that there is a difference in the population proportions. However, this difference might be too small to be meaningful—the statistically significant result does not tell us the size of the difference. Cohen's h, on the other hand, quantifies the size of the difference, allowing us to decide if the difference is meaningful.
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