# statsmodels.stats.weightstats.DescrStatsW.ztost_mean¶

method

DescrStatsW.ztost_mean(low, upp)[source]

test of (non-)equivalence of one sample, based on z-test

TOST: two one-sided z-tests

null hypothesis: m < low or m > upp alternative hypothesis: low < m < upp

where m is the expected value of the sample (mean of the population).

If the pvalue is smaller than a threshold, say 0.05, then we reject the hypothesis that the expected value of the sample (mean of the population) is outside of the interval given by thresholds low and upp.

Parameters
low, uppfloat

equivalence interval low < mean < upp

Returns
pvaluefloat

pvalue of the non-equivalence test

t1, pv1tuple

test statistic and p-value for lower threshold test

t2, pv2tuple

test statistic and p-value for upper threshold test