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, ‘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’.