statsmodels.stats.power.NormalIndPower

class statsmodels.stats.power.NormalIndPower(ddof=0, **kwds)

Statistical Power calculations for z-test for two independent samples

currently only uses pooled variance

Parameters:

ddofint, optional

Degrees of freedom correction for the standard deviation used in computing the effective sample size. Used, e.g., for a correlation coefficient where ddof=3.

**kwds

Additional keyword arguments passed to the Power base class.

Methods

plot_power([dep_var, nobs, effect_size, ...])	Plot power with number of observations or effect size on x-axis
power(effect_size, nobs1, alpha[, ratio, ...])	Calculate the power of a z-test for two independent sample
solve_power([effect_size, nobs1, alpha, ...])	Solve for any one parameter of the power of a two sample z-test

Methods

plot_power([dep_var, nobs, effect_size, ...])	Plot power with number of observations or effect size on x-axis
power(effect_size, nobs1, alpha[, ratio, ...])	Calculate the power of a z-test for two independent sample
solve_power([effect_size, nobs1, alpha, ...])	Solve for any one parameter of the power of a two sample z-test