Power Analysis Calculator

Published August 19, 2026

Calculate the required sample size, statistical power, or detectable effect size for a two-group comparison of independent means.

Calculate

Significance Level (α)

Test Direction

Two-sided

One-sided

Effect Size (Cohen’s d)

0.2 = small, 0.5 = medium, 0.8 = large

Sample Size Per Group

Enter the number of participants/subjects in each group.

Target Power

Required Sample Size Per Group

participants per group

Sample Size / Group 64

Total Sample Size 128

Statistical Power 80%

0% Power 80% 100% Power

Important: This calculator uses a normal-approximation method for two independent groups with equal sample sizes. For complex study designs, unequal group sizes, repeated measures, ANOVA, survival analysis, logistic regression, or non-inferiority studies, use an appropriate specialized power analysis method.

What is Statistical Power?

Statistical power is the probability of detecting a true effect when that effect actually exists. It is commonly expressed as 80%, 90%, or 95%. Higher power generally requires a larger sample size.

Cohen’s d represents the standardized difference between two group means. A commonly used interpretation is 0.2 for a small effect, 0.5 for a medium effect, and 0.8 for a large effect.

For many biomedical and pharmacological studies, researchers commonly consider a significance level of α = 0.05 and statistical power of at least 80%, although the appropriate values should be determined from the study protocol and research objectives.