During this project, I found myself questioning one of the statements of the tasks.

First, we use the 1-Sample T-Test to compare ‘vein_pack_lifespans’ to the average life expectancy ‘71’

Then, we check the p value of ‘vein_pack_test’. After that, is proceeds to the following task:

- We want to present this information to the CEO, Vlad, of this incredible finding. Let’s print some information out! If the test’s p-value is
**less**than 0.05,`print`

“The Vein Pack Is Proven To Make You Live Longer!”. Otherwise`print`

“The Vein Pack Is Probably Good For You Somehow!”

But looking at the documentation of the scipy function ttest_sample1 it says: " This is a two-sided test for the null hypothesis that the expected value (mean) of a sample of independent observations *a* is equal to the given population mean, *popmean* ."

From my understanding, if we do a two-sided test and reject the null hypothesis, we can’t be sure in what direction we should look at - is the life expectancy average greater than 71 or less than 71?