Multiple Linear Regression

  • Jobson J
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Abstract

The multiple linear regression model is the most commonly applied statistical technique for relating a set of two or more variables. In Chapter 3 the concept of a regression model was introduced to study the relationship between two quantitative variables X and Y. In the latter part of Chapter 3, the impact of another explanatory variable Z on the regression relationship between X and Y was also studied. It was shown that by extending the regression to include the explanatory variable Z, the relationship between Y and X can be studied while controlling or taking into account Z. In a multivariate setting, the regression model can be extended so that Y can be related to a set of p explanatory variables X1, X2, …, Xp. In this chapter, an extensive outline of the multiple linear regression model and its applications will be presented. A data set to be used as a multiple regression example is described next.

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Jobson, J. D. (1991). Multiple Linear Regression (pp. 219–398). https://doi.org/10.1007/978-1-4612-0955-3_4

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