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.

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