Statistical Power Calculator
Power or required sample size for t-tests, proportions and correlations.
Enter your values to see the result.
Means use the noncentral t distribution approximated by a shifted t; proportions use the normal approximation and correlations use Fisher's z. Results agree with G*Power to within about 1 percentage point.
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- Sample Size Calculator — Size prevalence, cohort and case-control studies.
- Effect Size Calculator — Estimate d from published results.
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Find steps, examples and limitations below.
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How to use the Statistical Power Calculator
Power or required sample size for t-tests, proportions and correlations.
- 1 Choose the design and whether to solve for power or sample size.
- 2 Enter the effect size (d, proportions or r) and alpha.
- 3 Read the power, or the sample size needed to reach your target power.
Example and practical tips
Detecting d = 0.5 with 50 people per group at α = 0.05 (two-sided) gives about 70% power; 64 per group are needed for 80%.
Frequently asked questions
What power should I aim for?
80% is the usual minimum and 90% is common in confirmatory trials. Lower power means a real effect is easily missed.
Where does the effect size come from?
From pilot data, earlier studies or the smallest effect that would matter in practice. Avoid inflated estimates from small studies.
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