Resources for learning R with Statistics

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Already read: Free resources for learning R

I would prefer to have a textbook which covers statistics with R, accessible to a beginning graduate student in statistics. Since I'm not as familiar with R as I should be, I will be purchasing A Beginner's Guide to R by Zuur, but what is a good text for covering statistics with R for a beginning graduate student?

@AleksandrBlekh - Assume I'm a prospective M.S. Statistics student who would like to do research in stochastic processes. — Clarinetist, Dec 22 '14 at 02:52
Andy Field's book is a good intro stats book and covers R ok. I know of nothing that really integrates the learning of stats using R well if that's what you're looking for. — John, Dec 22 '14 at 03:18
If you intend to use R seriously, I *highly recommend* you to reconsider the book by Zuur et al. in favor of [The Art of R Programming](http://www.amazon.com/The-Art-Programming-Statistical-Software/dp/1593273843) by Matloff. Not only the former is twice as expensive, but, more importantly, it covers less than half of the essential material in the latter, which I own. As for the Andy Field's book, I agree with @John that it's a good book, but I would consider it too simplistic for graduate level in statistics. — Aleksandr Blekh, Dec 22 '14 at 04:55

score 1 · Accepted Answer · answered Dec 22 '14 at 04:24

Your update (information on already read Q&As) as well as your statistics focus make it more difficult to recommend something that IMHO fits the level. The following books, which I have selected from a larger set, more or less satisfy your both requirements of being on "statistics with R" and at "M.S. Statistics" level are (though some are at or around an undergraduate level):

Probability and Statistics with R: http://www.routledge.com/books/details/9781584888918
Statistical Computing with R: http://www.routledgementalhealth.com/books/details/9781584885450
An Introduction to Statistical Learning with Applications in R (more basic): http://www-bcf.usc.edu/~gareth/ISL
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (more advanced): http://statweb.stanford.edu/~tibs/ElemStatLearn
An Introduction to Applied Multivariate Analysis with R: http://www.springer.com/statistics/statistical+theory+and+methods/book/978-1-4419-9649-7
Graphical Models with R (contains a chapter on stochastic models): http://www.springer.com/statistics/statistical+theory+and+methods/book/978-1-4614-2298-3

No R, but books, focused on stochastic processes or systems:

An Introduction to Stochastic Processes and Their Applications: http://www.springer.com/mathematics/probability/book/978-1-4613-9744-1
Convergence of Stochastic Processes: http://www.springer.com/mathematics/probability/book/978-1-4612-9758-1
Stochastic Orders: http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-32915-4

Also may be of interest (mostly R-based):

All of Statistics: A Concise Course in Statistical Inference (No R, but excellent book and includes a chapter on stochastic processes): http://link.springer.com/book/10.1007%2F978-0-387-21736-9
Modern Applied Statistics with S. Fourth Edition: http://www.stats.ox.ac.uk/pub/MASS4
A Modern Approach to Regression with R: http://www.stat.tamu.edu/~sheather/book
A Handbook of Statistical Analyses using R, Third Edition: http://www.crcpress.com/product/isbn/9781482204582
Computational Actuarial Science with R (bonus, based on your SE profile): http://www.routledgementalhealth.com/books/details/9781466592599

Resources for learning R with Statistics

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