BOOK CHAPTER

Chapter 3: The Multiple Linear Regression Model

Regression and Analysis of Variance

By Peter Goos and Ellen Vandervieren

Peter Goos
Peter Goos
Professor of Bio-Science Engineering
University of Leuven
Ellen Vandervieren
Associate Professor in Statistics and Mathematics Education
University of Antwerp

A previous chapter of the book demonstrated that the simple linear regression model is very useful. In some cases, however, the simple linear model can be improved upon by considering additional explanatory variables. In other words, it is sometimes possible to explain more of the variation in the response variable by including more than one explanatory variable in the regression model. In this chapter, we show how to generalize the simple linear regression model, involving just one explanatory variable, to a multiple linear regression model, involving more than one explanatory variable.

The focus in this chapter is on the use of multiple quantitative explanatory variables. It is possible to include qualitative explanatory variables in multiple regression models as well. We deal with qualitative (both nominal and ordinal) explanatory variables in Chapter 5.

Learning objectives of this chapter include:

Knowledge:

Skills

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