(This article was first published on

**Why? » R**, and kindly contributed to R-bloggers)My sabbatical is rapidly coming to an end, and I have to start thinking more and more about teaching. Glancing over my module description for the introductory computational statistics course I teach, I noticed that it’s a bit light on recommend/background reading. In fact it has only two 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.

What other good R books could I recommend? In particular, I’m looking for books that:

- Assume no prior knowledge of programming.
- Assume very little knowledge of statistics. For example, no regression.
- Doesn’t try to teach statistics. So no “R with ….” type books.
- Are cheap!

Suggestions welcome (needed!)

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