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.

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Yes, you can access The R Book by Elinor Jones, Simon Harden, Michael J. Crawley in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Wiley

Year

2022

ISBN

9781119634409

Edition

Topic

Computer Science

Subtopic

Computer Science General

Index

Computer Science

Cover
Title Page
Copyright
Contents
List of Tables
Preface
Acknowledgments
About the Companion Website
Chapter 1 Getting Started
Chapter 2 Technical Background
Chapter 3 Essentials of the R Language
Chapter 4 Data Input and Dataframes
Chapter 5 Graphics
Chapter 6 Graphics in More Detail
Chapter 7 Tables
Chapter 8 Probability Distributions in R
Chapter 9 Testing
Chapter 10 Regression
Chapter 11 Generalised Linear Models
Chapter 12 Generalised Additive Models
Chapter 13 Mixed‐Effect Models
Chapter 14 Non‐linear Regression
Chapter 15 Survival Analysis
Chapter 16 Designed Experiments
Chapter 17 Meta‐Analysis
Chapter 18 Time Series
Chapter 19 Multivariate Statistics
Chapter 20 Classification and Regression Trees
Chapter 21 Spatial Statistics
Chapter 22 Bayesian Statistics
Chapter 23 Simulation Models
Index
EULA