Statistical power calculators

Statistical Power Information Sample Size Calculators

#	Calculator	Relevant Tests
1	T 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)
2	Chi-Squared test power	Chi-Squared Test For Goodness Of Fit
3	Regression power, ANOVA power	Simple Linear Regression Multiple Linear Regression One way ANOVA
4	F test power	F test for variances
6	Proportion power	One sample proportion test. Two sample proportion test.

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.

The test power is the probability to reject the null assumption, H₀, when it is not correct.
Power = 1- β.
Researchers usually use the power of 0.8 which means the Beta level (β), the maximum probability of type II error, failure to reject an incorrect H₀, is 0.2.
The commonly used significance level (α), the maximum probability of type I error, is 0.05.
The Beta level (β) is usually four times as big as the significance level (α), since rejecting a correct null assumption consider to be more severe than failing to reject incorrect null assumption.

Power analysis chart

The calculators create the following dynamic chart:

Region of Acceptance - accept the null hypothesis if the statistic value in this area.
Region of Rejection - reject the null hypothesis if the statistic value in this area.
Grey area - The probability to accept the H₀ when H₀ is correct.
Significance level (α) - The probability to reject the H₀ when H₀ is correct.
β: the probability to accept the H₀ when H₁ is correct.
Test power: The probability to reject the H₀ when H₁ is correct.