[R] Recommendations regarding textbooks

[R. Michael Weylandt]

What level are you looking to teach?

MASS is fantastic but very terse; it presumes a good foundation in
statistics and deals mainly with the computational aspects. My guess
would be that this book would only really be suitable for a class with
a good pre-existing background knowledge who are willing to work-hard
and learn R quite rapidly. Once one's up to speed, however, it's a
pretty indispensable resource.

I don't know the other two books personally, but their authors are
quite well known in the R community and, like you, I've heard good
things about both [books]. Prof. Dalgaard is in R-Core and Prof. Fox
is an active package maintainer so they might jump in any minute to
clarify the level of their books.

Just browsing the ToC on Amazon, the subject matters also seem to be
somewhat different so it might also be worthwhile deciding which bits
of statistics your course aims to teach. If you can narrow down the
scope of the course you can probably get a better recommendation.

Hope this helps,
Michael

On Thu, Mar 22, 2012 at 8:17 AM, richard willey
<richard.willey at gmail.com> wrote:
> Hello
>
> I was hoping to get some advice regarding teaching R in an academic environment.
>
> What are the best choices with respect to textbooks?
>
> When this question was asked a few years back, people were primarily
> recommending “Modern Applied Statistics with S” and “Introductory
> Statistics with R” as two good choices.  I’ve also heard some good
> thinks regarding “An R Companion to Applied Regression”.
>
> Has anything else really good come along in recent years?
>
> Alternatively, are there any really good companion textbooks / lab
> manuals to accompany standard texts?
>
> Thanks in advance,
>
> Richard
>
>
>
> --
> I think back to the halcyon dates of my youth, when indeterminate
> Hessians had something to do with the Revolutionary War, where
> conjugate priors were monks who had broken their vows, and the
> expression (X'X)^-1(X'Y) was greek
>
> Those were simpler times
>
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