Summary

In this chapter, we talked all about hypothesis testing. We covered what it was, as well as a quick guide to the process of hypothesis testing. Next, we discussed a null hypothesis, an alternative hypothesis, and the difference between the two. Then you learned how the p-value is used to determine which hypothesis you accept and reject when compared to alpha. This led to type I and type II errors – what they are as well as how they interact with alpha. Finally, we went over what makes a good question for hypothesis testing and how to deal with a question that is less than ideal.

This has been a lot of theory in one chapter, but these are concepts that you must thoroughly understand, not only for the exam but also to perform any hypothesis testing as a data analyst. In the next chapter, we will cover some of the analyses you can use to perform a hypothesis test!