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Published in:
2023 | OriginalPaper | Chapter
5. Multiple Regression
Author : Daniel P. McGibney
Published in: Applied Linear Regression for Business Analytics with R
Publisher: Springer International Publishing
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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.