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on 28 October 2011
R is tough at the start, probably for longer than the start. I was completely new to any form of programming or indeed statistics beyond the rudimentary teaching at medical school that noone paid much attention to. However, thrust into a genomic scale PhD i found it almost mandatory to know something about R and statistics to convert data into knowledge. That said, one can try to leave it up to the purer bioinformaticians but its nice to have overlapping abilities and a way of deciphering certain research papers.

This book was my second book in R. The first was Beginning R, in the same series. I think they complement each other quite well but the first book is the weaker of the two, but still a relatively gentle introduction. This book also has excellent introduction chapters that might be enough for the savy given the wealth of additional material for free on the internet anyway.

The structure of this book is logical and whilst not going into statistics in vast amounts of detail the writing is so lucid and crisp that it feels like the information imparted is of a much greater tome.

I think going on an R course whilst reading this and the beginnings book is about the easiest way of entering the world of R. For more brief encounters one could simply just use individual packages without revising the whole of stats/R. Another good book in the series for the genomically orientated is the bioconductor case studies, although they all need modernising into the post-microarray, high throughput sequencing world.
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on 12 November 2010
Peter Dalgaard has written an excellent book. I read it in conjunction with O'Reilly's R in a Nutshell, and found myself getting into R at speed. It helps to have some knowledge of statistics before starting, but it is not essential.

Highly recommended.
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on 9 October 2009
If you are just starting out with R I can recommend this book. The presentation is very clear and concise, concentrating on the basics of getting things done rather than exploring the multitude of options available with every command. As a bonus all the datasets used in the book's examples can be easily downloaded from the R repository (it tells you how in the book), so you can work through them as you read. Although it's a relatively short book, it covers all of statistical analyses in common use, and it keeps the statistical theory to the minimum required to understand the models. I think this is the best introductory book on R I've come across.
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on 27 May 2011
This book is brilliant. It not only teaches the fundamentals of R but is also a great introduction to statistics. Can thoroughly recommend.
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on 22 January 2014
I have used R for about 10 years now for my research and I always turn back to this back for reminder on the small (but very important) things I always seems to forget.
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on 14 November 2010
As an MSc student using lots of stats programs, I found R to be the most straight forward. This book allows you to work through and learn how to complete all the tasks you will need, in a simple step-by-step way.
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on 27 October 2012
This is a very helpful book that can introduce you to R from scratch. It is very well written and every step is well described. For a very beginner like me it has been a surprise. Very useful book.
Enjoy R!!!!
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on 9 November 2014
good mix of R and statistics - but assumes some basic statistical knowledge. I've previously dabbled in both and it has just the right pace for me to make me stay interested and thinking.
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on 14 October 2012
Although there is no doubt that this book is an excellent introduction to the R programming language and follows a clear developmental path from the simple to the more complex, it is still quite tough. I had a real problem with the exercises at the end of the chapters which seemed to demand a greater level of knowledge and inference than that which was provided in the previous text (this accounts for the four stars).This was a little frustrating and maybe some more 'hints' could have been provided to make the process easier.
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on 9 December 2014
It tries to explain both statistics and R in one book and, in my opinion, fails at both. Better get a good statistics book and and a book or an online tutorial on R (if you really have to learn R), otherwise Python.
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