Multiple Regression

Daniel P. McGibney
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Daniel P. McGibney: University of Miami, Management Science

Chapter Chapter 5 in Applied Linear Regression for Business Analytics with Python, 2026, pp 113-137 from Springer

Abstract: 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.

Date: 2026
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DOI: 10.1007/978-3-032-23806-1_5

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