R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

From the Introduction

Welcome to the R Cookbook, 2nd Edition

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 10,000 available add-on packages, and R is a serious rival to all commercial statistical packages.

But R can be frustrating. It’s not obvious how to accomplish many tasks, even simple ones. The simple tasks are easy once you know how, yet figuring out that “how” can be maddening.

This book is full of how-to recipes, each of which solves a specific problem. Each recipe includes a quick introduction to the solution followed by a discussion that aims to unpack the solution and give you some insight into how it works. We know these recipes are useful and we know they work, because we use them ourselves.

The range of recipes is broad. It starts with basic tasks before moving on to input and output, general statistics, graphics, and linear regression. Any significant work with R will involve most or all of these areas.

If you are a beginner, then this book will get you started faster. If you are an intermediate user, this book will be useful for expanding your horizons and jogging your memory (“How do I do that Kolmogorov–Smirnov test again?”).

The book is not a tutorial on R, although you will learn something by studying the recipes. It is not a reference manual, but it does contain a lot of useful information. It is not a book on programming in R, although many recipes are useful inside R scripts.

Finally, this book is not an introduction to statistics. Many recipes assume that you are familiar with the underlying statistical procedure, if any, and just want to know how it’s done in R.

The Recipes

Most recipes use one or two R functions to solve a specific problem. It’s important to remember that we do not describe the functions in detail; rather, we describe just enough to solve the immediate problem. Nearly every such function has additional capabilities beyond those described here, and some have amazing capabilities.

We strongly urge you to read the functions’ help pages. You'll likely learn something valuable.

Each recipe presents one way to solve a particular problem. Of course, there are likely several reasonable solutions to each problem. When we knew of multiple solutions, we generally selected the simplest one. For any given task, you can probably discover several alternative solutions yourself. This is a cookbook, not a bible.

In particular, R has literally thousands of downloadable add-on packages, many of which implement alternative algorithms and statistical methods. This book concentrates on the core functionality available through the basic distribution combined with several important packages known collectively as the tidyverse.