Multiple Regression

In Chapter 13, you learn about multiple regression, which is the linear combination of two or more predictor variables to optimize the relationship between the observed and predicted variables. You also learn, as promised earlier, that the general linear model underlying multiple regression also underlies ANOVA and t tests, and you can use regression instead of those procedures to obtain the same (or more informative) results. You discover R’s functions for dealing with both continuous and dichotomous predictor variables, and how to dummy code your data to achieve the most useful information. As a bonus, I show ...

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