Introduction

So you’re holding a statistics book. In my humble (and absolutely biased) opinion, it's not just another statistics book. It’s also not just another R book. I say this for two reasons.

First, many statistics books teach you the concepts but don't give you an easy way to apply them. That often leads to a lack of understanding. Because R is ready-made for statistics, it’s a tool for applying (and learning) statistics concepts.

Second, let’s look at it from the opposite direction: Before I tell you about one of R’s features, I give you the statistical foundation it's based on. That way, you understand that feature when you use it — and you use it more effectively.

I didn’t want to write a book that only covers the details of R and introduces some clever coding techniques. Some of that is necessary, of course, in any book that shows you how to use a software tool like R. My goal was to go way beyond that.

Neither did I want to write a statistics “cookbook”: when-faced-with-problem-category-#152-use-statistical-procedure-#346. My goal was to go way beyond that, too.

Bottom line: This book isn't just about statistics or just about R — it’s firmly at the intersection of the two. In the proper context, R can be a great tool for teaching and learning statistics, and I’ve tried to supply the proper context.

About This Book

Although the field of statistics proceeds in a logical way, I’ve organized this book so that you can open it up in any chapter and start reading. The idea is for you to find the information you're looking for in a hurry and use it immediately — whether it's a statistical concept or an R-related one.

On the other hand, reading from cover to cover is okay if you're so inclined. If you're a statistics newbie and you have to use R to analyze data, I recommend that you begin at the beginning.

Similarity with This Other For Dummies Book

You might be aware that I’ve written another book: Statistical Analysis with Excel For Dummies (Wiley). This is not a shameless plug for that book. (I do that elsewhere.)

I’m just letting you know that the sections in this book that explain statistical concepts are much like the corresponding sections in that one. I use (mostly) the same examples and, in many cases, the same words. I’ve developed that material during decades of teaching statistics and found it to be very effective. (Reviewers seem to like it, too.) Also, if you happen to have read the other book and you’re transitioning to R, the common material might just help you make the switch.

And, you know: If it ain’t broke… .

What You Can Safely Skip

Any reference book throws a lot of information at you, and this one is no exception. I intended for it all to be useful, but I didn't aim it all at the same level. So if you're not deeply into the subject matter, you can avoid paragraphs marked with the Technical Stuff icon.

As you read, you'll run into sidebars. They provide information that elaborates on a topic, but they're not part of the main path. If you're in a hurry, you can breeze past them.

Foolish Assumptions

I'm assuming this much about you:

How This Book Is Organized

I’ve organized this book into five parts and three appendixes (which you can find on this book’s companion website at www.dummies.com/go/statisticalanalysiswithr).

Part 1: Getting Started with Statistical Analysis with R

In Part 1, I provide a general introduction to statistics and to R. I discuss important statistical concepts and describe useful R techniques. If it’s been a long time since your last course in statistics or if you’ve never even had a statistics course, start with Part 1. If you have never worked with R, definitely start with Part 1.

Part 2: Describing Data

Part of working with statistics is to summarize data in meaningful ways. In Part 2, you find out how to do that. Most people know about averages and how to compute them. But that's not the whole story. In Part 2, I tell you about additional statistics that fill in the gaps, and I show you how to use R to work with those statistics. I also introduce R graphics in this part.

Part 3: Drawing Conclusions from Data

Part 3 addresses the fundamental aim of statistical analysis: to go beyond the data and help you make decisions. Usually, the data are measurements of a sample taken from a large population. The goal is to use these data to figure out what's going on in the population.

This opens a wide range of questions: What does an average mean? What does the difference between two averages mean? Are two things associated? These are only a few of the questions I address in Part 3, and I discuss the R functions that help you answer them.

Part 4: Working with Probability

Probability is the basis for statistical analysis and decision-making. In Part 4, I tell you all about it. I show you how to apply probability, particularly in the area of modeling. R provides a rich set of capabilities that deal with probability. Here's where you find them.

Part 5: The Part of Tens

Part V has two chapters. In the first, I give Excel users ten tips for moving to R. In the second, I cover ten statistical- and R-related topics that wouldn't fit in any other chapter.

Online Appendix A: More on Probability

This online appendix continues what I start in Part 4. The material is a bit on the esoteric side, so I’ve stashed it in an appendix.

Online Appendix B: Non-Parametric Statistics

Non-parametric statistics are based on concepts that differ somewhat from most of the rest of the book. In this appendix, you learn these concepts and see how to use R to apply them.

Online Appendix C: Ten Topics That Just Didn't Fit in Any Other Chapter

This is the Grab Bag appendix, where I cover ten statistical- and R-related topics that wouldn't fit in any other chapter.

Icons Used in This Book

Icons appear all over For Dummies books, and this one is no exception. Each one is a little picture in the margin that lets you know something special about the paragraph it sits next to.

tip This icon points out a hint or a shortcut that can help you in your work (and perhaps make you a finer, kinder, and more insightful human being).

remember This one points out timeless wisdom to take with you on your continuing quest for statistics knowledge.

warning Pay attention to the information accompanied by this icon. It's a reminder to avoid something that might gum up the works for you.

technicalstuff As I mention in the earlier section “What You Can Safely Skip,” this icon indicates material you can blow past if it’s just too technical. (I’ve kept this to a minimum.)

Where to Go from Here

You can start reading this book anywhere, but here are a couple of hints. Want to learn the foundations of statistics? Turn the page. Introduce yourself to R? That's Chapter 2. Want to start with graphics? Hit Chapter 3. For anything else, find it in the table of contents or the index and go for it.

In addition to what you’re reading right now, this product comes with a free access-anywhere Cheat Sheet that presents a selected list of R functions and describes what they do. To get this Cheat Sheet, visit www.dummies.com and type Statistical Analysis with R For Dummies Cheat Sheet in the search box.