Effect Size Calculator

From Means & SDs From a t-value

Group 1

Mean

Standard Deviation

Sample Size

Group 2

Mean

Standard Deviation

Sample Size

About This Tool

What Is Cohen's d?

Cohen's d measures the size of the difference between two groups' means, in standard-deviation units. Unlike a p-value, which only tells you whether a difference is statistically significant, effect size tells you how big that difference actually is — and it doesn't shrink just because your sample got bigger.

When to Use It

Reporting effect size alongside a t-test result, as most journals and dissertation committees expect
Comparing the practical importance of results across different studies
Power analysis and study planning

Cohen's (1988) Benchmarks

|d| < 0.2 — negligible
0.2 – 0.5 — small
0.5 – 0.8 — medium
> 0.8 — large

The Formula

\( d = \dfrac{M_1 - M_2}{SD_{pooled}} \), \( SD_{pooled} = \sqrt{\dfrac{(n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}} \)

Worked Example

Method A: 25 students, mean 78, SD 10. Method B: 25 students, mean 72, SD 9.

Pooled SD ≈ 9.51
d = (78−72) / 9.51 ≈ 0.63
By Cohen's benchmarks, that's a medium effect — a real, practically meaningful difference between the methods.

Your Results

Cohen's d

What This Means

Where It Falls on Cohen's Scale

Perfect for students, researchers, and professionals looking to build real statistical skills.

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