In a recent post, I asked for suggestions for introductory R computing books. In particular, I was looking for books that:

- Assume no prior knowledge of programming.
- Assume very little knowledge of statistics. For example, no regression.
- Are cheap, since they are for undergraduate students.

Some of my **cons** aren’t really downsides as such. Rather, they just indicate that the books aren’t suitable for this particular audience. A prime example is “R in a Nutshell”.

I ended up recommending five books to the first year introductory R class.

## Recommended Books

- A first course in statistical programming with R (Braun & Murdoch)
**Pros:**I quite like this book (hence the reason I put it on my list). It has a nice collection of exercises, it “looks nice” and doesn’t assume knowledge of programming. It also doesn’t assume (or try to teach) any statistics.**Cons:**When describing**for**loops and**functions**the examples aren’t very statistical. For example, it uses Fibonacci sequences in the**while**loop section and the sieve of Eratosthenes for**if**statements.

- An introduction to R (Venables & Smith)
**Pros:**Simple, short and to the point. Free copies available. Money from the book goes to the R project.**Cons**: More a R reference guide than a textbook.

- A Beginner´s Guide to R by Zuur.
**Pros:**Assumes no prior knowledge. Proceeds through concepts slowly and carefully.**Cons:**Proceeds through concepts**very**slowly and carefully.

- R in a Nutshell by Adler.
- I completely agree with the recent review by Robin Wilson: “Very comprehensive and very useful, but not good for a beginner. Great book though – definitely has a place on my bookshelf.”

**Pros:**An excellent reference.**Cons:**Only suitable for students with a previous computer background.

- Introduction to Scientific Programming and Simulation Using R by Jones, Maillardet and Robinson.
**Pros:**A nice book that teaches R programming. Similar to the Braun & Murdoch book.**Cons:**A bit pricey in comparison to the other books.

## Books not being recommended

These books were mentioned in the comments of the previous post.

- The Basics of S-PLUS by Krause & Olson.
- Most students struggle with R. Introducing a similar, but slightly different language is too sadistic.

- Software for Data Analysis: Programming with R by Chambers.
- Assumed some previous statistical knowledge.

- Bayesian Computation with R by Albert.
- Not suitable for first year students who haven’t taken any previous statistics courses.

- R Graphics by Paul Murrell
- I know graphics are important, but a whole book for an undergraduate student might be too much. I did toy with the idea of recommending this book, but I thought that five recommendations were more than sufficient.

- ggplot2 by Hadley Wickham.
- Great book, but our students don’t encounter ggplot2 in their undergraduate course.

## Online Resources

- Introduction to Probability and Statistics by Kerns
- Suitable for a combined R and statistics course. But I don’t really do much stats in this module.

- The R Programming wikibook (a work in progress).
- Will give the students this link.

- Biological Data Analysis Using R by Rodney J. Dyer. Available under the CC license.
- Nice resource. Possibly a little big for this course (I know that this is very picky, but I had to draw the line somewhere). Will probably use it for future courses.

- Hadley Wickham’s devtools wiki (a work in progress).
- Assumes a good working knowledge of R

- The R Inferno by Patrick Burns
- Good book, but too advanced for students who have never programmed before.

- Introduction to S programming
- It’s in french – this may or may not be a good thing depending on your point of view 😉

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I have found R in Action by Robert Kabacoff to be an excellent resource. Discounts are available – at times. As a pdf one can search with it, which helps when you may know the command but have trouble with the syntax. He has the same information on his web site (for free) and that was what I used prior. I have found his examples to be quite good.

Comment by Doug Lawson — January 29, 2011 @ 4:07 am

Thanks. Do you have a link to the pdf? I couldn’t find it.

Comment by csgillespie — February 17, 2011 @ 1:29 pm

His website is:

http://www.statmethods.net/

The link to his book is at the bottom left of the page. Unfortunately the book does cost. Of the books I have on R, it is my go-to source and has been worth the cost. I would think for an educator you might be able to get a deal (free for you or discount for students).

Doug

Comment by Doug Lawson — February 17, 2011 @ 3:03 pm

The first book I picked up on R was Modern Applied Statistics with S-PLUS by Venables and Ripley. No one would claim it’s suitable for beginners, but I had never heard of R before, and it got me interested in learning more. The book also contained a lot of topics in statistics that I had never encountered before. Made me want to learn about those too.

Unfortunately it’s not cheap, but most universities do have libraries 🙂

Comment by John S. — January 29, 2011 @ 5:45 am

[…] the beginner, but probably also for the more advanced user, this post on R Why gives an interesting list with recommended R computing books. Check it […]

Pingback by Nice list of R programming books | Ecostudies — January 29, 2011 @ 9:01 am

You should have named this post “R books for undergraduate students”. How come that “R in a Nutshell” made it to recommended list (and you have a typo there), and ggplot2 didn’t? I also disagree about “Bayesian Computation with R”. And you should definitely put http://www.statmethods.net in online resource list (unless you’re advertising Kabacoff’s book :-D).

Comment by aL3xa — January 29, 2011 @ 11:03 am

Thanks for the comments. Good point about the title (which I’ve now changed).

1. R in a Nutshell. Each year, I always have two or three very good computing students in the class. They can already program in C/Java, and so for the most part this course is a breeze. However, their statistical knowledge is almost non-existent. I thought that R in a Nutshell would introduce them to concepts about R programming (S3 objects for example), without clouding the issue with statistical topics.

2. ggplot2: I did consider it, but this book would only be suitable for the few students who find the course easy. Also, I didn’t want to recommend lots of books – I think that five might be too many.

3. Bayesian Computation with R: This is the

firststatistics course these students have (the other first year stats course we have runs in parallel). When I see the students for the first time, they have never even seen a probability distribution. Never mind likelihoods.4. I didn’t know about the statmethods.net site. Thanks.

5. I just did a quick calculation. For the two R books I bought to do this post, I will need another two years worth of advertising fees 😦 I suppose I shouldn’t give up my day job!

Comment by csgillespie — January 29, 2011 @ 11:25 am

Oh, sorry ’bout the 3rd one, I thought about “Introduction to Applied Bayesian Statistics and Estimation for Social Scientists” by Lynch. Anyway, that’s also too much for the first course. IPSUR is another good & free book: http://ipsur.r-forge.r-project.org/book/

And about a year ago I created some kind of recommendation list/wishlist on SO (and won a Necromancer badge for it :-D): http://stackoverflow.com/questions/192369/books-for-learning-the-r-language/2270793#2270793

Comment by aL3xa — January 29, 2011 @ 10:47 pm

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Pingback by Tweets that mention R books for undergraduate students « Why? -- Topsy.com — January 29, 2011 @ 10:38 pm

Hi,

I surprised no one has mentioned either Introductory Statistics with R by Peter Dalgaard or Using R for introductory statistics by John Verzani. I’m currently working my way through UsingR (see http://bit.ly/iefoP4), which I’m finding quite good. It’s clearly written and easy enough for beginners in both stats and programming.

-Chris

Comment by Chris — February 10, 2011 @ 8:27 pm

I was really after books that didn’t try to teach statistics *and* R. I find that many students have difficultly creating functions, for loops, if statements, when the mathematics is already familiar – never-mind when it’s new.

Comment by csgillespie — February 17, 2011 @ 1:31 pm

I really like Michael Crawley’s “Statistics: an introduction using R”. It teaches statistics in a nice informal way, intended for biological scientists, and you learn R along the way. Crawley teaches the craft of statistics, rather than the formal aspects. I’m surprised at how rarely this and its big brother “The R book3” get recommended. I love them both.

Comment by Alan Parker — April 12, 2011 @ 5:59 pm

My new favorite R book, at least for those with a programming background and interested in really learning the ins and outs of R, is

Norman Matloff’s The Art of R Programming, a tour of statisical software design.

Comment by Carol Munroe — March 12, 2012 @ 3:38 am