Summary

We covered a lot of information in this chapter. First, we talked about t-tests and how they are used to see whether there is a significant difference between two groups that use numeric variables. Then, we ran right into chi-square tests, and how they have two main types: chi-square goodness of fit and chi-square test for independence. A chi-square goodness of fit test sees whether a sample is a good representation of a population, while a chi-square test for independence compares two categorical variables to see whether there is a relationship between them. Next, we talked about correlation and how it can be used to see whether two numeric variables are related and how strongly they are related. Finally, we talked about simple linear regression and how it can be used to see whether one numeric variable can predict another. This wraps up everything you need to know about analyzing data for the exam.

In the next chapter, we will move on to reporting data!