Effect Size (Cohen's d) Calculator
Calculate Cohen's d and Hedges' g effect sizes for the difference between two independent group means, using pooled standard deviation.
Results
What is it?
Cohen's d is a standardized measure of the difference between two group means: d = |mean1 - mean2| / pooled_SD. It tells you how many standard deviations apart the two groups are, independent of sample size. Hedges' g corrects for the positive bias in Cohen's d when sample sizes are small.
How to use
Enter the mean, standard deviation, and sample size for each group. The calculator uses the pooled standard deviation formula: s_p = sqrt(((n1-1)*s1^2 + (n2-1)*s2^2) / (n1+n2-2)). Both Cohen's d and the bias-corrected Hedges' g are shown.
Example scenario
Treatment group (n=30, mean=105, SD=15) vs control (n=30, mean=100, SD=12). Pooled SD = sqrt((29*225 + 29*144)/58) = sqrt(184.5) = 13.58. Cohen's d = |105-100|/13.58 = 0.368 (small-medium effect). Hedges' g = 0.368 x (1 - 3/(4x60-9)) = 0.368 x 0.9874 = 0.364.
Pro tip
Cohen's d benchmarks (Cohen 1988): 0.2 = small, 0.5 = medium, 0.8 = large. In medicine and psychology, even d=0.2 can be clinically important if the outcome is serious. For sample sizes below 20 per group, prefer Hedges' g over Cohen's d -- the difference can be substantial. Report effect sizes alongside p-values; a study can be statistically significant (p<0.05) with a trivially small effect size (d<0.1) if n is large enough.