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4.6 out of 5 stars
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on 19 April 2012
Andy Field's previous SPSS textbook is one of the best books on statistical methods that I have ever read, and I am very pleased to say that, after reading his new (along with co-authors Jeremy Miles and Zoe Field) book on R, he has kept his high standards of writing and clear, concise, and extremely useful explanations.

If you 1) need to learn statistics, 2) need to learn how to perform statistical analysis, and 3) need to do them in R, then this is the book to buy!
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on 13 April 2015
I first came across Andy Field through "Discovering Statistics Using SPSS". Lately, I have dived into "Discovering Statistics Using R", which is, in my opinion, basically the same book using a different software. Which is not half-bad as it is a good book (both of them). Now, of course, R is becoming increasingly popular as a powerful statistical package available to anyone for free, but remains difficult to master because of the unfamiliar interface for most people not raised as programmers. Thus, writing an introductory book about statistics using R is definitely a challenge where one needs to weigh conflicting interests. The authors have to a large degree succeeded. The book combines introduction to statistics and introduction to R in a good way, and it is certainly a book that will serve both purposes well. However, there are especially two issues that should be taken into consideration when/if revising the book. (1) Learning R is so much more easy if using R Studio - there is many things that will seem easier to the R novice if using R Studio. (2) Unfortunately, this book follows in the foosteps of several (most?) other introductory books on statistics by being superficial (and to some degree even wrong) when discussing assumptions. In this book for instance, on p.167, the authors claim: "If you use a parametric test when your data are not parametric then the results are likely to be inaccurate". There is a very long debate among staticians and practitioners of statistical analyses regarding the robustness of parametric tests. Without aiming at solving that discussion here, there is plenty of empirical reserach showing that the claim made by the authors are unwarranted, and a discussion on assumptions (especially in introductory books) should be much more nuanced. On assumptions, the authors also claim bluntly that an assumption of using parametric tests is that "Data should be measured at least at the interval level" (p.168), obviously falling back on the taxonomy by Stevens (1946). Again, to simply claim this regarding assumptions of parametric tests without reservations or discussion is fallacious. Introductory books on statistics, including this book, need to include a more nuanced view on assumptions, as users of the book otherwise get a wrong idea about assumptions.
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on 8 November 2013
Recommended for students in any discipline requiring stats, and lecturers for preparing the course.

I've found this book a god-send. I'm teaching a statistics course and up till this book I just picked at the useful bits, but, didn't know them in any real detail. This book has helped me to gain the fine detail needed to prepare lectures and answer questions. Its also written in such a way that I can just sit down with a coffee and plough through a chapter without stopping, which is rare for me.

Best book I have bought this year, one of the best text books I have ever bought.
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on 29 September 2015
I would love to give this book more stars, there is a lot of information here and the authors have clearly tried hard to explain things. I am reasonably numerate but haven't spent much time with stats and now find myself needing to learn both stats and R.

Unfortunately there is just too much verbiage in the book to make it a useful reference or book for self study. It is very hard to find a concise explanation anywhere in the book. If you are reasonably numerate avoid this book and look elsewhere, you will only be frustrated by ploughing through paragraphs when a couple of equations could explain the point much more effectively. I made it to chapter 7 by force of will, but will now look elsewhere for something that fits my learning style better. So far the best bet seems to be Crawley's Statistics an Introduction Using R.

The book reads like a cook book - lots of recipes but precious little hard explanation of why things are the way they are. For me the low point came when the authors claimed not to know why minimizing the sum of squares resulted in the regression equations, something covered in most calculus courses.

An irritant is the fact that the book ignores R Studio, this makes scripting in R much easier for a beginner. Another nagging point is the authors' reliance on packages, when much can be done with the basic functionality in R.
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on 1 February 2014
I'd never studied any statistics before buying this book and my knowledge of stats was *very* basic to say the least. This book is a beast - it's huge, but if you bother to spend the time reading it, it gives you a fantastic and extensive introduction to statistics as well as helping with more advanced problems that you might have. It's easy to read and the theory behind the statistical tests is very clearly set out. I had a couple of problems where the commands written in the book wouldn't work on my version of R, but this is just because R is open source so advances very quickly. A quick search on the internet normally solves the problem.
The author is perhaps a bit too friendly at times and this approach to writing academic text books normally annoys me, but in this case I have to concede it was quite refreshing amongst the stats nightmares I was having. This book has pretty much been my bible for the last 4 months and I'm not sure where I'd be without it. The same review goes for Andy Field's equivalent book on SPSS - again, amazing.
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on 21 January 2014
Reviewed for the Social Research Association by Paul Webb, Research Officer, Praxis Care, Belfast

Easy to read, entertaining and brim full of information. This book will appeal to the statistics neophyte and to the seasoned data analyst irrespective of subject discipline. The authors skilfully describe how to conduct quantitative analyses using R whilst showing how the base capabilities of R can be extended using a plethora of packages.
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on 22 August 2016
Surprisingly readable despite the complex stats on offer!

Makes learning stats again (almost) fun and well worth the effort.

And besides I now know the approximate ejaculate of Japanese quail, which is sure to come up in the pub quiz.
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on 31 March 2014
Having spent a decade teaching undergraduates the joy of statistics, I would not be without this book. I recommend it every year to my students as a resource they should be able to access. It's not something you carry around between home and uni - Andy gives you value for money in this enormous tome. However, it is a resource you keep returning to for humorous, articulate advice on both statistics and how to code for specific analyses in R.
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on 27 July 2012
I purchased this book as someone who is passably statistics conversant, but hasn't previously had any experience of R. I have to admit that I do find the writers style a little wearing - the continual slightly smutty "student language" reminds me very much of a group of small children trying to shock adults. I guess that there must be some who enjoy it as the book seems to sell well.

More critically, I do find that it is oriented very strongly to social scientists. As a physical scientist, I do battle to find relevant examples in the text. All despite it being a truly doorstop sized book - not something to carry around for odd moments when you want to delve into the programming.

So overall - okay, but not a great book. I'm sure there is a market for another author to try his hand in.
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on 25 August 2014
I have been using SPSS since the 1970's (with occasional forays into STATA and SAS). I can't afford SPSS for my personal use, so taking the plunge into R is a "no-brainer" for me. This book is a great introduction to R. I particularly like Andy Field's irreverent humour. I do accept that it might not work for everybody - see the reviews...
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