Page 99 - Statistics II for Dummies

Chapter 5

Multiple Regression with

Two X Variables

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.

Getting to Know the Multiple

Regression Model

Before you jump right into using the multiple regression model, get a feel for
what it’s all about. In this section, you see the usefulness 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 regression model (see Chapter
4). Some of the concepts are a little more complex, as you may guess because
the model is more complex. But the concepts and the results should make
intuitive sense, which is always good news.

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