Cohen's d Calculator

Cohen's d is a standardized effect size that measures the difference between two group means in units of pooled standard deviation. You calculate it as d = (mean1 minus mean2) divided by the pooled SD. Because it is standardized, you can compare effect sizes across studies that use different scales.

The pooled standard deviation combines the spread of both groups, weighted by their degrees of freedom. The formula is the square root of ((n1 minus 1) times SD1 squared plus (n2 minus 1) times SD2 squared) divided by (n1 plus n2 minus 2). This calculator uses the sample standard deviation, which divides by n minus 1.

By Jacob Cohen's 1988 benchmarks, an absolute d below 0.2 is negligible, 0.2 to 0.5 is small, 0.5 to 0.8 is medium, and 0.8 or above is large. These are general rules of thumb, so always interpret the size in the context of your field, since a small d can still matter for some outcomes.

Hedges' g is Cohen's d with a correction for small-sample bias, since d tends to overestimate the true effect when sample sizes are small. The calculator multiplies d by the factor 1 minus 3 divided by (4 times df minus 1), where df is n1 plus n2 minus 2. For large samples the two values are nearly identical, so g is preferred when groups are small.

Yes. Switch the input type to raw data and paste two lists of numbers, separated by commas or spaces. The calculator computes each group's mean and sample standard deviation, then derives Cohen's d and Hedges' g. Each group needs at least two values.

The sign only tells you which group has the higher mean. A positive d means group 1 scored higher, and a negative d means group 2 scored higher. The magnitude rating (small, medium, large) uses the absolute value, so the size of the effect is the same regardless of the sign.