stats.power.NormalIndPower()

statsmodels.stats.power.NormalIndPower

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

Statistical Power calculations for z-test for two independent samples.

currently only uses pooled variance

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 t-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 t-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