This book is about the R programming language. Maybe more important, this book is for you.
These days, R is an impressively robust language for solving problems that lend themselves to statistical
programming methods. There is a large community of users and developers of this language, and together
we are able to accomplish things that were not possible before we virtually met.
Of course, to leverage this collective knowledge, we have to start somewhere. Chapters 1 through 5
focus on gaining familiarity with the R language itself. If you have prior experience in programming, these
chapters will be very easy for you. If you have no prior programming experience, that is perfectly fine.
We build from the ground up, and let us suggest you spend some thoughtful time here. Thinking like a
programmer has some very great advantages. It is a skill we would want you to have, and this book is,
after all, for you.
Chapters 6 through 10 focus on what might be termed elementary statistical methods in R. We did not
have the space to introduce those methods in their entirety—we are supposing some knowledge of statistics.
An introductory or elementary course for nonmajors would be more than enough. If you are already familiar
with programming and statistics, we suggest you travel through these chapters only briefly.
With Chapter 11, we break into the last part of the book. For someone with both a fair grasp of traditional
statistics and some programming experience, this may well be a good place to start. For our readers who
read through from the first pages, this is where it starts to get very exciting. From bootstrapping to logistic
regression to data visualization to high-performance computing, these last chapters have hands-on examples
that work through some much applied and very interesting examples.
One final note: While we wrote this text from Chapter 1 to Chapter 19 in order, the chapters are fairly
independent of each other. Don't be shy about skipping to the chapter you're most interested in learning.
We show all our code, and you may well be able to modify what we have to work with what you have.
Happy reading
