Chapter 8. Regression
This chapter covers
- Fitting and interpreting linear models
- Evaluating model assumptions
- Selecting among competing models
In many ways, regression analysis lives at the heart of statistics. It’s a broad term for a set of methodologies used to predict a response variable (also called a dependent, criterion, or outcome variable) from one or more predictor variables (also called independent or explanatory variables). In general, regression analysis can be used to identify the explanatory variables that are related to a response variable, to describe the form of the relationships involved, and to provide an equation for predicting the response variable from the explanatory variables.
For example, an exercise physiologist ...
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