In this chapter, you examined a business scenario using SLR with one predictor variable and one response variable. You began by understanding the basic components of a simple linear regression including model formulation, inspection, interpretation, and diagnostics. You then learned how to determine whether the data met all the necessary assumptions for liner models, as well as how to use the model to predict outcomes and quantify your confidence in the results.

In situations where the data violated any assumptions, you learned how to transform the data using a structured approach. You also learned how to identify anomalous data known as outliers and determine whether they were influential points. Finally, you began to learn about models that have more than one predictor variable and required multiple linear regression.

In the next chapter, you will learn a different type of modeling called cluster analysis. It is useful for data that has very different characteristics and cannot be...