statsmodels.stats.power.TTestIndPower.power¶

TTestIndPower.
power
(effect_size, nobs1, alpha, ratio=1, df=None, alternative='twosided')[source]¶ Calculate the power of a ttest for two independent sample
Parameters: effect_size : float
standardized effect size, difference between the two means divided by the standard deviation. effect_size has to be positive.
nobs1 : int or float
number of observations of sample 1. The number of observations of sample two is ratio times the size of sample 1, i.e.
nobs2 = nobs1 * ratio
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.
ratio : float
ratio of the number of observations in sample 2 relative to sample 1. see description of nobs1 The default for ratio is 1; to solve for ratio given the other arguments, it has to be explicitly set to None.
df : int or float
degrees of freedom. By default this is None, and the df from the ttest with pooled variance is used,
df = (nobs1  1 + nobs2  1)
alternative : string, ‘twosided’ (default), ‘larger’, ‘smaller’
extra argument to choose whether the power is calculated for a twosided (default) or one sided test. The onesided test can be either ‘larger’, ‘smaller’.
Returns: 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.