statsmodels.stats.proportion.proportions_ztost(count, nobs, low, upp, prop_var='sample')[source]

Equivalence test based on normal distribution


count : integer or array_like

the number of successes in nobs trials. If this is array_like, then the assumption is that this represents the number of successes for each independent sample

nobs : integer

the number of trials or observations, with the same length as count.

low, upp : float

equivalence interval low < prop1 - prop2 < upp

prop_var : string or float in (0, 1)

prop_var determines which proportion is used for the calculation of the standard deviation of the proportion estimate The available options for string are ‘sample’ (default), ‘null’ and ‘limits’. If prop_var is a float, then it is used directly.


pvalue : float

pvalue of the non-equivalence test

t1, pv1 : tuple of floats

test statistic and pvalue for lower threshold test

t2, pv2 : tuple of floats

test statistic and pvalue for upper threshold test


checked only for 1 sample case