5 Regression models
This chapter covers
- Identifying and treating outliers
- Running and interpreting statistical tests of normality
- Computing and visualizing correlations between continuous variables
- Fitting and interpreting multiple linear regressions
- Fitting and interpreting regression trees
In this chapter, we’ll demonstrate how to fit regression models, namely, multiple linear regressions and regression trees. Our dependent, or target, variable will be regular season wins, and our independent variables, or predictors, will be the full complement of hustle statistics that the NBA began recording during the 2016-17 season. These statistics include but aren’t limited to blocked shots, deflections, and loose balls recovered. Hence, we’ll be regressing ...
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