13.1 AN OVERVIEW OF GENERAL LINEAR MODELS
In Chapter 11, the linear regression models we examined each had a continuous response variable. However, what happens if we want to build a regression model for a binary response instead? Or for a numeric discrete response? Luckily, there is a family of linear models that includes all three cases – continuous, numeric discrete, and binary – of regression response variables: General Linear Models (GLMs).
To explain how regression for three different kinds of responses can be related, we will briefly take another look at the parametric regression equations for each case. Once we establish how they are related, we will then use their descriptive versions, just as we did in Chapter 11.
Recall the parametric model for multiple regression, given here.
![equation](https://static.packt-cdn.com/products/9781119526810/graphics/images/c13-disp-0001.png)
The sum β0 + β1x1 + β2x2 + ⋯ + βpxp is called...