statsmodels.stats.weightstats.ztost

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

Equivalence test based on normal distribution

Parameters:

• x1 (array_like or None) – one sample or first sample for 2 independent samples

• low (float) – equivalence interval low < m1 - m2 < upp

• upp (float) – equivalence interval low < m1 - m2 < upp

• x1 – second sample for 2 independent samples test. If None, then a one-sample test is performed.

• usevar (str, 'pooled') – If pooled, then the standard deviation of the samples is assumed to be the same. Only pooled is currently implemented.

Returns:

• 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