Cohen’s d for independent samples t-test

Cohen’s Standards for Small, Medium, and Large Effect Sizes

Cohen’s d is a measure of effect size based on the differences between two means. Cohen’s d, named for United States statistician Jacob Cohen, measures the relative strength of the differences between the means of two populations based on sample data. The calculated value of effect size is then compared to Cohen’s standards of small, medium, and large effect sizes.

Cohen’s d is the measure of the difference between two means divided by the pooled standard deviation:

Concept Review

Two population means from independent samples where the population standard deviations are not known

• Random Variable: X̄1 - X̄2, the difference of the sampling means

• Distribution: Student’s t-distribution with degrees of freedom (variances not pooled)

Formula Review

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