ABSTRACT

A Hands-On Way to Learning Data AnalysisPart 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

chapter 1|12 pages

Introduction

chapter 2|20 pages

Estimation

chapter 3|18 pages

Inference

chapter 4|8 pages

Prediction

chapter 5|14 pages

Explanation

chapter 6|26 pages

Diagnostics

chapter 7|14 pages

Problems with the Predictors

chapter 8|20 pages

Problems with the Error

chapter 9|16 pages

Transformation

chapter 10|12 pages

Model Selection

chapter 11|22 pages

Shrinkage Methods

chapter 12|14 pages

Insurance Redlining — A Complete Example

chapter 13|8 pages

Missing Data

chapter 14|18 pages

Categorical Predictors

chapter 15|12 pages

One Factor Models

chapter 16|16 pages

Models with Several Factors

chapter 17|14 pages

Experiments with Blocks