Power Analysis Calculator
Calculate statistical power for study planning.
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Enter the expected effect size (Cohen's d), sample size per group, and significance level. The calculator estimates the statistical power, the probability of detecting a real effect. A power of 0.80 or higher is typically considered adequate.
About This Calculator
Statistical power is the probability of correctly rejecting a false null hypothesis (detecting a real effect). It depends on effect size, sample size, and significance level. Power analysis is essential for planning studies: too small a sample means low power and a high chance of missing a real effect.
Frequently Asked Questions
What is Cohen's d?
Cohen's d measures effect size as the difference between means divided by the pooled standard deviation. Small = 0.2, medium = 0.5, large = 0.8.
What power should I aim for?
The convention is 0.80 (80%). Some fields recommend 0.90 or higher for critical decisions.
How do I increase power?
Increase sample size, use a larger significance level (trade-off with Type I error), increase effect size through better measurement, or use a one-tailed test if justified.