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.
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 ...