Field, A., Miles J., Field, Z. (2012) Discovering statistics using R
This book teaches statistics by using R – the free statistical environment and programming language. It will be of use to undergraduate and postgraduate students and professional researchers across the social sciences, including material which ranges from the introductory to the advanced. Divided into four levels of difficulty with ‘Level 1’ representing introductory material and ‘Level 4’ the most advanced material, it may be read from beginning to end or with reference to particular techniques. An understanding of the advanced material may require knowing the material in earlier chapters. There is a comprehensive glossary of specialised terms and a selection of statistical tables in the appendix. There is also material on the publisher’s companion website and on the principal author’s own web pages.
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 are entertaining references 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. This is an achievement when one considers that R can be difficult to use for researchers who have never manipulated data from the command line. Another plus point is that the authors describe how to ‘extend’ R’s capabilities with ‘packages’. This is a massive time saver for any researcher who does not know which package is required in order to extend R’s base system to conduct a particular test. Field et al. also succeed in placing many of the statistical procedures to which they allude within the framework of the ‘general linear model’ giving the book a sense of theoretical coherence.
But I think that the book would have benefited from an explanation of how R fits into the wider ‘tool chain’ of public domain programs which can be used to produce a publication-ready paper. Moreover, some of the exemplars of R code may not work or may be illustrative of deprecated techniques but the principal author is maintaining an errata file on his own website. Nevertheless, I would recommend this book to students, academics and applied researchers. Although heavily weighted towards the interests of psychological researchers, it would not be too difficult to transfer the techniques to a different area of expertise. All in all, an invaluable resource.
Review originally published in Research Matters, December 2013