Linear Models with R

A Hands-On Way to Learning Data Analysis

Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.

New to the Second Edition

• Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality
• Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates
• Extensive us