Mastering Data Analysis with R

Chapter 6. Beyond the Linear Trend Line (authored by Renata Nemeth and Gergely Toth)

Linear regression models, which we covered in the previous chapter, can handle continuous responses that have a linear association with the predictors. In this chapter, we will extend these models to allow the response variable to differ in distribution. But, before getting our hands dirty with the generalized linear models, we need to stop for a while and discuss regression models in general.

The modeling workflow

First, some words about the terminology. Statisticians call the Y variable the response, the outcome, or the dependent variable. The X variables are often called the predictors, the explanatory variables, or the independent variables. Some of the predictors ...