Introduction to Regression Modeling with R (Preliminary Edition)

The primary goal of Introduction to Regression Modeling with R is to help students understand the types of questions regression models can and cannot answer and how to answer them. Students will become familiar with fitting both simple and complex models using R. The text stresses model interpretation rather than tedious algebra or mathematics since R calculates almost all relevant numbers. Equations are presented to help flesh out the "why" behind various aspects of modeling...
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The primary goal of Introduction to Regression Modeling with R is to help students understand the types of questions regression models can and cannot answer and how to answer them. Students will become familiar with fitting both simple and complex models using R. The text stresses model interpretation rather than tedious algebra or mathematics since R calculates almost all relevant numbers. Equations are presented to help flesh out the "why" behind various aspects of modeling and to provide additional insights into how regression models work.

Introduction to Regression Modeling with R includes numerous examples and sections not featured in earlier editions, and R code is visible throughout the book. A custom R package accompanies the text and was written to aid in regression model building and interpretation. This text is intended for those studying for professions that make use of large and potentially complex datasets arising observational studies, particularly in the fields of business and social science.