Preface
PART I THE LANGUAGE
1 Getting Started
2 Numerics, Arithmetic, Assignment, and Vectors
3 Matrices and Arrays
4 Non-numeric Values
5 Lists and Data Frames
6 Special Values, Classes, and Coercion
7 Basic Plotting
8 Reading and Writing Files
PART II PROGRAMMING
9 Calling Functions
10 Conditions and Loops
11 Writing Functions
12 Exceptions, Timings, and Visibility
PART III STATISTICS AND PROBABILITY
13 Elementary Statistics
14 Basic Data Visualization
15 Probability
16 Common Probability Distributions
PART IV STATISTICAL TESTING AND MODELING
17 Sampling Distributions and Confidence
18 Hypothesis Testing
19 Analysis of Variance
20 Simple Linear Regression
21 Multiple Linear Regression
22 Linear Model Selection and Diagnostics
PART V ADVANCED GRAPHICS
23 Advanced Plot Customization
24 Going Further with the Grammar of Graphics
25 Defining Colors and Plotting in Higher Dimensions
26 Interactive 3D Plots
APPENDICES
A Installing R and Contributed Packages
B Working with RStudio
Bibliography
Tilman M. Davies is a senior lecturer at the University of Otago in New Zealand, where he teaches statistics and R at all university levels. He has been programming in R for 10 years and uses it in all of his courses.
“You must see this epic work...a game changer.”
—Kirk Borne, Principal Data Scientist at Booz Allen Hamilton
“Extremely well written with excellent explanations and examples,
this book fully accomplishes the goal of providing the reading with
both the programming and statistical skills required to become
proficient with this language. I am nothing short of amazed at the
consistent quality and clarity of the text and the utility of the
exercises.”
—Computerworld
"The Book of R is a gentle yet informative introduction to the
statistical software environment R. It is for anyone interested in
programming, statistics, and data analysis, and is especially
well-suited for students and instructors of statistics
courses."
—Timothy King, Solutions Review
“I’ve been looking for a book like this for some time. It fills
some holes in my course content that my own book doesn’t
address.”
—insideBIGDATA
“I recommend this book to both beginners, as a good introduction to
basic statistics and R, and to intermediate users as a desktop
reference to assist in performing day-to-day analysis.”
—One R Tip a Day
“Overall, The Book of R is an excellent reference for novice data
analysts and for students being introduced to statistical
programming tools.”
—Harry J. Foxwell, ACM's Computing Reviews
"Because it has a clearly defined structure, one can easily focus
on aspects of specific interest . . . And this is, in fact, what
the author intended: to serve a variety of audiences that would be
interested in the dual aspects of using R as both a programming
language and as a tool for statistical problem solving. In this
regard, the book serves these audiences well, including students,
researchers, and practitioners of both computing and statistical
methods."
—Janusz Zalewski, ACM's Computing Reviews
“The book is therefore addressing two audiences with different
needs – coders who might need help with understanding statistical
concepts and statisticians of one breed or another who want to
learn how to code. Satisfying both groups is a big ask, but Tilman
Davies pulls it off.”
—Network Security Newsletter
“Davies' book is perhaps the most comprehensive explanation of the
core R language in print, and an excellent introduction to using R
for statistical programming.”
—Oliver Keyes, sociotechnical systems researcher
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