Hypothesis Testing

This chapter is all about the basic concepts behind hypothesis testing. Some data analyst positions will have little to no hypothesis testing, but this is really where data analysts shine. You receive a question, create a hypothesis, sometimes run a study, analyze data, and give a report that allows someone to make an informed decision. This process is the heart of data analytics, even if the majority of your time will be spent on more mundane tasks.

Here, we will discuss what hypothesis testing is and how it relates to the null hypothesis and the alternative hypothesis. Then, we will cover p-value and alpha and their role in hypothesis testing. Next, we will discuss type I and type II errors, how you can adjust them, and how they impact your hypothesis testing. Finally, we will go over how to write a question that will lead to a clean and accurate hypothesis test.

In this chapter, we’re going to cover the following main topics:

• Understanding...