## a null hypothesis with a 99% probability to be true…

**W**hen checking the Python t distribution random generator, np.random.standard_t(), I came upon this manual page, which actually does not explain how the random generator works but spends instead the whole page to recall Gosset’s *t* test, illustrating its use on an energy intake of 11 women, but ending up misleading the readers by interpreting a .009 one-sided p-value as meaning “the null hypothesis [on the hypothesised mean] has a probability of about 99% of being true”! Actually, Python’s standard deviation estimator x.std() further returns by default a non-standard standard deviation, dividing by n rather than n-1…

March 28, 2018 at 7:06 pm

Ahah stick with R :-)

March 28, 2018 at 3:00 pm

J’ai aussi eu ce problème de calcul de l’écart-type dans Maple. Maple ne donne pas la même réponse pour Var(X) et Cox(X,X) basée sur des données, divisant par n-1 dans le premier cas et par n pour le second.