Selected Amazon Reviews of the R Book by Michael J. Crawley

R book

I am a beginner at R and taking classes online to become proficient at using the programming language. This book is so clear for a beginner and moves up rapidly into great detail on each of topic, that I am using it as a checklist for my mathematics course meaning it is written in such a way that you can use it to build up on subject you my have forgotten about or need focusing on. The array of example for how to write functions, setting up environments, characters, text, strings, vector functions, matrices and arrays..Every R student and statistician has to have this book.

Kevin Wrighton October 21, 2014

Better name would be "Intro to data analysis using R"

1. The content of this book is similar to an earlier book by the same author (Statistical Computing: An Introduction to Data Analysis using S-Plus), but now capitalizing on the popularity of R The earlier book had a much more appropriate name, as the focus of the book is on data analysis (with R), not on R itself. People reading this book hoping to learn R will be disappointed. The book is best for people who have a rudimentary knowledge of R and want to learn about the many methods for analyzing data in R. The excellent breadth of coverage means that there is not a great deal of depth for any particular topic.
2. The R code makes extensive use of the "attach" function to attach data frames. This is nearly a cardinal sin, for it leads to a cluttered work environment. This is a carryover from the very ancient way of doing things in S-Plus. It's really not that hard to add "data= " arguments to the function calls, or use the "with" function.
3. Some people have had trouble finding the datasets used in the book. The general trend these days is that book authors often create an R package containing the data used in the book. I suggest this be done for any future edition of the book.

The R Book  by Michael J. Crawley

Let me first say that I've been in the software world for 44-years, so I've used a bunch of software, and had to learn most of it on my own. To me, how good docs are in explaining a software product is paramount. Now, I do use commercial statistics packages and they are either very good with docs or there are a number of useful books available to assist in learning and/or using the package.

R was recommended to me years ago, and my first exposure to it was disappointing. There was little available in learning docs and the online help to me was worthless (sidebar: I still believe the online help is worthless).

Then came Crawleys book. Everything I wanted to know was explained with hundreds of worked examples. And, that was the first edition. The second edition contains more worked examples, and you can try them yourself, using the data sets that Dr. Crawley makes freely available from his website (but not all files. Some appear to be missing).

That said, I now use R regularly, and believe that I might not have without this book. For anyone wanting an excellent book explaining R, I have not found one better.

By Dimitri Shvorob on January 14, 2013

... And I am referring to more advanced statistics than data summarization, and I am also distinguishing statistics from machine learning (or "statistical learning", as Hastie and Tibshirani call it) methods. "The R Book" provides a reliable introduction to R, although I prefer Robert Kabacoff's "R in Action", and, secondly, think that "R for Everyone" by Jared Lander is a necessary intermediate read, as both "R Book" and "R in Action", unfortunately, skip over some very useful utilities, including "ggplot2" graphics package.

An excellent introduction to analysing and understanding your data if you're a novice, and an excellent reference to how to get things done if you're not.

The book is easy to follow. You're guided through how the statistics work from first principles, and then walked through what the output from R means. This means you get a thorough understanding of what's going on to begin with, and then can get things done quickly and with confidence on your own data.

The colour throughout makes it easy to follow, and the index is very comprehensive so it's easy to find things. The book is very thorough on things like ANOVAs and generalised linear models, and gives a good amount of detail on most things you could want to know (spatial, multivariate, Bayesian, time series, etc.).

If you're serious about statistics, you're never going to be able to find everything you need in one book, and maybe that's no problem in these days of the internet. However, this is the closest thing to a complete reference I've ever found, and I'm always coming back to it. Yes, it's a little more pricey than some others out there, but the quality and depth of coverage mean it's worth it in my opinion.

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