Statistical power calculators

The power calculator computes the test power based on the sample size and draw an accurate power analysis chart.
Larger sample size increases the statistical power.

Researchers usually use the power of 0.8 which mean the probability of type II error (β), failure to reject an incorrect H0.2, is 0.2. The commonly used significant level (α) is 0.05. β is usually four times bigger than α, since rejecting a correct null assumption consider to be more severe than failing to reject a correct invalid assumption.

#CalculatorRelevant TestsChart
1T test power
Z test power
One Sample Z-Test
One Sample T-Test
Two Sample Z-Test
Two Sample T-Test (Pooled variance)
Two Sample T-Test (Welch's)
t Distribution
2Chi-Squared test powerChi-Squared Test For Goodness Of FitChi squared Distribution
3Regression powerSimple Linear Regression
Multiple Linear Regression
f Distribution
4F test powerF test for variancesf Distribution