From t to p
Previously, you calculated the test statistic for the two-sample problem of whether the mean weight of shipments is lower 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
.
This exercise is part of the course
Hypothesis Testing in R
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