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Discovering Statistics Using R Paperback – 22 Mar 2012

4.5 out of 5 stars 31 customer reviews

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Product details

  • Paperback: 992 pages
  • Publisher: SAGE Publications Ltd; 1 edition (22 Mar. 2012)
  • Language: English
  • ISBN-10: 1446200469
  • ISBN-13: 978-1446200469
  • Product Dimensions: 3.8 x 19 x 25.4 cm
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (31 customer reviews)
  • Amazon Bestsellers Rank: 19,475 in Books (See Top 100 in Books)
  • See Complete Table of Contents

Product Description


In statistics, R is the way of the future. The big boys and girls have known this for some time: There are now millions of R users in academia and industry. R is free (as in no cost) and free (as in speech). Andy, Jeremy, and Zoe's book now makes R accessible to the little boys and girls like me and my students. Soon all classes in statistics will be taught in R.

I have been teaching R to psychologists for several years and so I have been waiting for this book for some time. The book is excellent, and it is now the course text for all my statistics classes. I'm pretty sure the book provides all you need to go from statistical novice to working researcher.

Take, for example, the chapter on t-tests. The chapter explains how to compare the means of two groups from scratch. It explains the logic behind the tests, it explains how to do the tests in R with a complete worked example, which papers to read in the unlikely event you do need to go further, and it explains what you need to write in your practical report or paper. But it also goes further, and explains how t-tests and regression are related---and are really the same thing---as part of the general linear model. So this book offers not just the step-by-step guidance needed to complete a particular test, but it also offers the chance to reach the zen state of total statistical understanding.

Prof. Neil Stewart
Warwick University

Field's Discovering Statistics is popular with students for making a sometimes deemed inaccessible topic accessible, in a fun way. In Discovering Statistics Using R, the authors have managed to do this using a statistics package that is known to be powerful, but sometimes deemed just as inaccessible to the uninitiated, all the while staying true to Field's off-kilter approach.

Dr Marcel van Egmond
University of Amsterdam

Probably the wittiest and most amusing of the lot (no, really), this book takes yet another approach: it is 958 pages of R-based stats wisdom (plus online accoutrements)... A thoroughly engaging, expansive, thoughtful and complete guide to modern statistics. Self-deprecating stories lighten the tone, and the undergrad-orientated 'stupid faces' (Brian Haemorrhage, Jane Superbrain, Oliver Twisted, etc.) soon stop feeling like a gimmick, and help to break up the text with useful snippets of stats wisdom. It is very mch a student textbook but it is brilliant... Field et al. is the complete package.
David M. Shuker
AnimJournal of Animal Behaviour

"This work should be in the library of every institution where statistics is taught. It contains much more content than what is required for a beginning or advanced undergraduate course, but instructors for such courses would do well to consider this book; it is priced comparably to books which contain only basic material, and students who are fascinated by the subject may find the additional material a real bonus. The book would also be very good for self-study. Overall, an excellent resource." (R. Bharath Choice 2012-12-01)

The main strength of this book is that it presents a lot of information in an accessible, engaging and irreverent way. The style is informal with interesting excursions into the history of statistics and psychology. There is reference to research papers which illustrate the methods explained, and are also very entertaining. The authors manage to pull off the Herculean task of teaching statistics through the medium of R... All in all, an invaluable resource. (Paul Webb 2013-12-12)

About the Author

Andy Field is Professor of Child Psychopathology at the University of Sussex. He has published over 80 research papers, 29 book chapters, and 17 books mostly on child emotional development and statistics. 

He is the founding editor of the Journal of Experimental Psychopathology and has been an associate editor and editorial board member for the British Journal of Mathematical and Statistical Psychology, Cognition and Emotion, Clinical Child and Family Psychology Review and Research Synthesis Methods. 

His ability to make statistics accessible and fun has been recognized with local and national teaching awards (University of Sussex, 2001, 2015, 2016; the British Psychological Society, 2007), a prestigious UK National Teaching Fellowship (2010), and the British Psychological Society book award (2006). He adores cats (and dogs), and loves to listen to and play very heavy music. He lives in Brighton with his wonderful wife Zoë, his son Zach, his crazy spaniel Ramsey and Fuzzy the cat.

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Customer Reviews

Top Customer Reviews

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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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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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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.Read more ›
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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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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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