WooCommerce Post-Purchase Survey: 7 Questions, When to Ask and What to Do Next Effect size calculator
Calculate Cohen's d and Hedges' g for a difference in means. The effect size shows how much the difference matters in practice, not only whether it is statistically significant.
Group summary data
Control or old version
Standard deviation
Number of observations
Test or new version
Standard deviation
Number of observations
Interpretation
Change the inputs to recalculate.
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How Cohen's d is calculated
Formula
Cohen's d = (meanB − meanA) / pooled SD. Hedges' g = d × a small-sample correction.
Cohen's d
Shows by how many standard deviations the group means differ.
Hedges' g
Similar to d, with a correction for small samples.
Practical significance
Even a statistically significant result can be too small to act on.
Calculation examples
1 New onboarding
2 New call-to-action text
What to avoid
- Looking only at the p-value The p-value is about statistical confidence; the effect size is about the scale of the difference.
- Comparing metrics without context d standardizes the difference, but the business meaning of different metrics still differs.
- Ignoring the direction A positive d here means group B is higher than A. Check that this is the direction you want.
Frequently asked questions
How do I interpret Cohen's d?
How is Hedges' g different from Cohen's d?
Can I calculate d for a 1–5 scale?
Why can an effect be small with a significant p-value?
What should I report alongside the effect size?
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