TTestPower.power(effect_size, nobs, alpha, df=None, alternative='two-sided')[source]

Calculate the power of a t-test for one sample or paired samples.


standardized effect size, mean divided by the standard deviation. effect size has to be positive.

nobsint or float

sample size, number of observations.

alphafloat in interval (0,1)

significance level, e.g. 0.05, is the probability of a type I error, that is wrong rejections if the Null Hypothesis is true.

dfint or float

degrees of freedom. By default this is None, and the df from the one sample or paired ttest is used, df = nobs1 - 1

alternativestr, ‘two-sided’ (default), ‘larger’, ‘smaller’

extra argument to choose whether the power is calculated for a two-sided (default) or one sided test. The one-sided test can be either ‘larger’, ‘smaller’. .


Power of the test, e.g. 0.8, is one minus the probability of a type II error. Power is the probability that the test correctly rejects the Null Hypothesis if the Alternative Hypothesis is true.

Last update: Dec 14, 2023