Publisher's Synopsis
Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied.
Uses numerous graphs in R to illustrate the model's results, assumptions, and other features.
Does not assume a background in calculus or linear algebra; rather, an introductory statistics course and familiarity with elementary algebra are sufficient.
Provides many examples using real world datasets relevant to various academic disciplines.
Fully integrates the R software environment in its numerous examples.
