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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