Using SciPy for common hypothesis testing

The previous section went over a t-test and the basic concepts in general hypothesis testing. In this section, we are going to fully embrace the powerful idea of the paradigm of hypothesis testing and use the SciPy library to solve various hypothesis testing problems.

The paradigm

The powerful idea behind the hypothesis testing paradigm is that if you know that your assumption when hypothesis testing is (roughly) satisfied, you can just invoke a well-written function and examine the P-value to interpret the results.

Tip

I encourage you to understand why a test statistic is built in a specific way and why it follows a specific distribution. For example, for the t-distribution, you should understand what the DOF is. However, this will require a deeper understanding of mathematical statistics. If you just want to use hypothesis testing to gain insights, knowing the paradigm is enough.

If you want to apply hypothesis testing...