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Multiple Regression

In: Applied Linear Regression for Business Analytics with R

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  • Daniel P. McGibney

    (University of Miami)

Abstract

In this chapter, we build upon the coverage of regression analysis by considering situations involving two or more predictor variables. For instance, while the weight of a person may be predicted using their height, we could use both the height and age of that person to predict their weight. Using more than one predictor variable to predict a response is called multiple regression analysis, which enables us to consider more predictor variables and thus obtain better estimates than those possible with simple linear regression.

Suggested Citation

  • Daniel P. McGibney, 2023. "Multiple Regression," International Series in Operations Research & Management Science, in: Applied Linear Regression for Business Analytics with R, chapter 0, pages 91-113, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-21480-6_5
    DOI: 10.1007/978-3-031-21480-6_5
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