Effect Size Calculator
Compute Cohen's d, the standardized difference between two group means.
Input Data
Mean of group 1.
SD of group 1 (>0).
Size of group 1.
Mean of group 2.
SD of group 2 (>0).
Size of group 2.
Results
0.4527
At a glance:Cohen's d = (x̄₁−x̄₂)/sₚ, where sₚ is the pooled standard deviation.
Formula
d = (x̄₁ − x̄₂) / sₚ
$$d = \frac{\bar{x}_1 - \bar{x}_2}{s_p}$$How to Use
- Enter the means, standard deviations and sample sizes of the two groups.
- The calculator outputs Cohen's d.
- Interpret using the common benchmarks: |d|≈0.2 small, 0.5 medium, 0.8 large.
- Combine with the t-test p-value to separate 'is it significant' from 'how large is the effect'.
FAQ
Why do we need an effect size?
The p-value only shows whether a result is unlikely due to chance; with large samples even tiny differences become significant. Effect size measures the actual magnitude, guarding against 'false significance' from big samples.
Where do Cohen's d benchmarks come from?
0.2 / 0.5 / 0.8 are Cohen's rules of thumb (small/medium/large) and are only guidelines; what counts as 'large' varies by field (in medicine 0.1 may already matter).
References
Content reviewed by the Calculatorism editorial team. Results are for reference only; please refer to the relevant authorities for the official figures.