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Author:   Tilman M. Davies
Publisher:   No Starch Press,US
Imprint:   No Starch Press,US
Weight:   0.369kg
ISBN:  

9781718503687

ISBN 10:   1718503687
Pages:   908
Publication Date:   25 November 2025
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   To order  
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Table of Contents

Preface Acknowledgments Introduction PART I: THE LANGUAGE Chapter 1: Getting Started Chapter 2: Numerics, Arithmetic, Assignment, and Vectors Chapter 3: Matrices and Arrays Chapter 4: Non-Numeric Values Chapter 5: Lists and Data Frames Chapter 6: Special Values, Classes, and Coercion Chapter 7: Basic Plotting Chapter 8: Reading and Writing Files PART II: PROGRAMMING Chapter 9: Calling Functions Chapter 10: Conditions and Loops Chapter 11: Writing Functions Chapter 12: Exceptions, Timings, and Visibility PART III: STATISTICS AND PROBABILITY Chapter 13: Elementary Statistics Chapter 14: Basic Data Visualizations Chapter 15: Probability Chapter 16: Common Probability Distributions PART IV: STATISTICAL TESTING AND MODELING Chapter 17: Sampling Distributions and Confidence Chapter 18: Hypothesis Testing Chapter 19: Analysis of Variance Chapter 20: Simple Linear Regression Chapter 21: Multiple Linear Regression Chapter 22: Linear Model Selection and Diagnostics PART V: ADVANCED GRAPHICS Chapter 23: Advanced Plot Customization Chapter 24: Going Further with the Grammar of Graphics Chapter 25: Defining Colors and Plotting in Higher Dimensions Chapter 26: Interactive 3D Plots Appendix A: Installing R and Contributed Packages Appendix B: Working with RStudio Reference List

Reviews

“A game changer.” —Kirk Borne, principal data scientist at Booz Allen Hamilton

Author Information

Tilman M. Davies is an academic at the Department of Mathematics and Statistics at the University of Otago in New Zealand, where he teaches statistics at all university levels. He has been programming in R since the early 2000s and uses it in all of his courses. Davies has received multiple significant research grants for his methodological work in spatial statistics and in 2024 received the Littlejohn Award, the premier research award of the New Zealand Statistical Association.

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