From t to p

Previously, you calculated the test statistic for the two-sample problem of whether the mean weight of shipments is smaller for shipments that weren't late (late == "No") compared to shipments that were late (late == "Yes"). In order to make decisions about it, you need to transform the test statistic with a cumulative distribution function to get a p-value.

Recall the hypotheses:

\(H_{0}\): The mean weight of shipments that weren't late is the same as the mean weight of shipments that were late.

\(H_{A}\): The mean weight of shipments that weren't late is less than the mean weight of shipments that were late.

The test statistic, t_stat, is available, as are the samples sizes for each group, n_no and n_yes. Use a significance level of alpha = 0.05.

t has also been imported from scipy.stats.