The R Book

A start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields

In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive discussion of foundational and advanced topics in the R software language, which is used widely in science, engineering, medicine, economics, and other fields. The book is designed to be used as both a complete text—readable from cover to cover—and as a reference manual for practitioners seeking authoritative guidance on particular topics.

This latest edition offers instruction on the use of the RStudio GUI, an easy-to-use environment for those new to R. It provides readers with a complete walkthrough of the R language, beginning at a point that assumes no prior knowledge of R and very little previous knowledge of statistics. Readers will also find:

• A thorough introduction to fundamental concepts in statistics and step-by-step roadmaps to their implementation in R;
• Comprehensive explorations of worked examples in R;
• A complementary companion website with downloadable datasets that are used in the book;
• In-depth examination of essential R packages.

Perfect for undergraduate and postgraduate students of science, engineering, medicine economics, and geography, The R Book will also earn a place in the libraries of social sciences professionals.

Elinor Jones, PhD, is an Associate Professor (Teaching) in the Department of Statistical Science at University College London. She is an experienced teacher with a background in statistics consultancy in a range of fields.

Simon Harden, PhD, is an Associate Professor (Teaching) in the Department of Statistical Science at University College London. He has taught R and statistics to people with a wide range of backgrounds, and has experience working in finance and IT.

Michael J Crawley FRS is Emeritus Professor of Plant Ecology at Imperial College London.

Preface

1 Getting started 1

2 Technical background 17

3 Essentials of the R language 55

4 Data input and dataframes 195

5 Graphics 235

6 Graphics in more detail 289

7 Tables 357

8 Probability distributions in R 369

9 Testing 401

10 Regression    433

11 Generalised Linear Models 495

12 Generalised Additive Models 575

13 Mixed-effect models 599

14 Non-linear regression 627

15 Survival analysis 651

16 Designed experiments 669

17 Meta-analysis 701

18 Time Series 717

19 Multivariate Statistics 743

20 Classification and regression trees 765

21 Spatial Statistics 785

22 Bayesian Statistics 807

23 Simulation models 833

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.