# statsmodels.stats.weightstats.ztost¶

statsmodels.stats.weightstats.ztost(x1, low, upp, x2=None, usevar='pooled', ddof=1.0)[source]

Equivalence test based on normal distribution

Parameters: x1 (array_like or None) – one sample or first sample for 2 independent samples upp (low,) – equivalence interval low < m1 - m2 < upp x1 – second sample for 2 independent samples test. If None, then a one-sample test is performed. usevar (string, 'pooled') – If pooled, then the standard deviation of the samples is assumed to be the same. Only pooled is currently implemented. 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

Notes

checked only for 1 sample case