Discovering Statistics Using R
- Andy Field - University of Sussex, UK
- Jeremy Miles - RAND Corporation, USA
- Zoë Field - University of Sussex, UK
Watch Andy talk about the new version of his book for R: click here!
Hot on the heels of the award-winning and best selling Discovering Statistics Using SPSS Third Edition, Andy Field has teamed up with Jeremy Miles (co-author of Discovering Statistics Using SAS) to write Discovering Statistics Using R. Keeping the uniquely humorous and self-depreciating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using the freeware R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioral sciences throughout the world.
The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next the importance of exploring and graphing data will be discovered, before moving onto statistical tests that are the foundations of the rest of the book (for e.g. correlation and regression). Readers will then stride confidently into intermediate level analyses such as ANOVA, before ending their journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help the reader gain the necessary conceptual understanding of what they're doing, the emphasis is on applying what's learned to playful and real-world examples that should make the experience more fun than expected.
Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more (at www.uk.sagepub.com/dsur/).
Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
Supplements
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."
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.
This book will most certainly be adopted as the main course book. It covers the topics needed for my course rather comprehensive, with a closer look on the regression assumptions (how to test them and what to do when they are violated) as well as some extensions to ordinary OLS and logistic regression. It could be a little lengthy sometimes, and it is not always very well structured. I think that the book would benefit from an update (the 5th edition of the SPSS-version of this book looks much better, and I’m looking forward to a similar update of this R-version).
However, the combination of a well written textbook that also is helps the student to practically implement the knowledge in R makes it a book well worth adopting.
If we had used Stata in the course instead, I think that I had adopted “Applied Statistics Using Stata” by Mehmetoglu and Jakobsen. And if that book had existed in a R-version, I might have adopted that one instead. However, the book at hand (Field et. al.) is definitely well suited for the course as well. I’m looking forward to the next edition.
This textbook is easy-to-understand, and it is written in a humorous way. It has all the information needed for an easy comprehension of statistical intricacies. The book also comes with vast database that can be used by students to test their knowledge of the material, and/or how to operate R.
As I'm sure you know, R does more sophisticated statistical techniques for free that mainstream packages do not and so is potentially useful to the doctoral students I teach and supervise. An intermediate step is to use the R links in Field's SPSS book but in the end it is necessary to get to grips with R and this book is a relatively painless way of doing this (especially if you and/or your students are familiar with Fields SPSS book).
Discovering Statistics using R is an excellent book to engage students in learning statistics using top of the line software. The content is presented in a clear and coherent way, and the exercises help reinforce and consolidate knowledge in quite a funny way. It is great material for teaching and learning, but also a handy reference book for researchers.
As an open source software and with a vast supporting community, R is increasingly adopted by researchers. Discovering Statistics Using R allows a soft transition from other statistical softwares to this open source alternative.
Clear and easy to use as an alternative to using SPSS for my psychology students
This book covers the material we need, with plenty of exercises, accessible explanations. Most importantly, it describes and teaches the R statistics platform integrated with the rest of the text.
