statsmodels.stats.weightstats.DescrStatsW.ttost_mean¶
method
-
DescrStatsW.
ttost_mean
(low, upp)[source]¶ test of (non-)equivalence of one sample
TOST: two one-sided t 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, pv1, df1tuple
test statistic, pvalue and degrees of freedom for lower threshold test
- t2, pv2, df2tuple
test statistic, pvalue and degrees of freedom for upper threshold test