statsmodels.stats.power.TTestIndPower.power¶
- TTestIndPower.power(effect_size, nobs1, alpha, ratio=1, df=None, alternative='two-sided')[source]¶
Calculate the power of a t-test 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
orfloat
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
orfloat
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
str
, ‘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’.
- effect_size
- 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.
- power