statsmodels.stats.power.TTestPower.power¶

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.

Parameters:

effect_sizefloat: 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’. .

Returns:

powerfloat: 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.