Xi'an's Og

When 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…

This entry was posted on March 28, 2018 at 12:18 am and is filed under Books, R, Statistics, University life with tags cross validated, hypothesis testing, np.random.standard_t, null hypothesis, numpy, p-value, pseudo-random generator, Python, R, t distribution, W. Gosset, x.std. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.