Effect size calculator — Cohen's d, Hedges' g, r
Enter the mean, SD and n of two groups to get the standardized mean difference — Cohen’s d with a 95% confidence interval, the small-sample-corrected Hedges’ g, and the equivalent r.
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When to use this
Use this whenever you need a standardized mean difference: reporting your own two-group result (most journals and APA 7 require an effect size next to every t-test), extracting effect sizes from published papers for a meta-analysis (means, SDs and ns are usually all a paper gives you), or judging whether a statistically significant finding is practically meaningful. Because d is in standard deviation units it can be compared across studies that used different measurement scales.
Key assumptions
- Two independent groups (for pre–post designs, d computed this way ignores the correlation between measures).
- Pooled SD assumes roughly similar variances in the two groups.
- Cohen's benchmarks (0.2 / 0.5 / 0.8) are conventions, not laws — field-specific norms matter more.
Common mistakes
- Reporting d from tiny samples without the Hedges' correction — d is biased upward when n < 20 per group.
- Treating a significant p-value as evidence of a large effect — significance reflects n as much as magnitude.
- Comparing d values across studies whose control groups differ wildly in variability.
Frequently asked questions
What is the difference between Cohen's d and Hedges' g?
How do I convert d to r or to an odds ratio?
Is a negative d a problem?
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