The R Book
  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

About this 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.

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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

Table of contents

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