power(effect_size, nobs, alpha, df=None, alternative='two-sided')¶
Calculate the power of a t-test for one sample or paired samples.
effect_size : float
standardized effect size, mean divided by the standard deviation. effect size has to be positive.
nobs : int or float
sample size, number of observations.
alpha : float 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.
df : int 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
alternative : string, ‘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 : float
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.