Exercise

# 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`

.

Instructions 1/3

## Question

What type of test does the alternative hypothesis indicate that we need?