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Chapter 5
When Two Variables Are Better
than One: Multiple Regression
In This Chapter
Getting the basic ideas behind a multiple regression model
Finding, interpreting, and testing coefficients
Checking model fit
he idea of regression is to build a model that estimates or predicts one
Tquantitative variable (y) by using at least one other quantitative variable
(x). Simple linear regression uses exactly one x variable to estimate the y
variable. (See Chapter 4 for all the information you need on simple linear
regression.) Multiple linear regression, on the other hand, uses more than
one x variable to estimate the value of y.
In this chapter, you see how multiple regression works and how to apply it to
build a model for y. You see all the steps necessary for the process, including
determining which x variables to include, estimating their contributions to
the model, finding the best model, using the model for estimating y, and
assessing the fit of the model. It may seem like a mountain of information, but
you won’t regress on the topic of regression if you take this chapter one step
at a time.

The Multiple Regression Model

Before being able to jump right into using the multiple regression model, its
good to get a feel for what it’s all about. In this section, you see the useful-
ness of multiple regression as well as the basic elements of the multiple
regression model. Some of the ideas are just an extension of the simple linear

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