# Discovering Statistics Using R

- Andy Field - University of Sussex, UK
- Jeremy Miles - RAND Corporation, USA
- Zoë Field - University of Sussex, UK

Keeping the uniquely humorous and self-deprecating 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 R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.

The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on *applying* what you learn to playful and real-world examples that should make the experience more fun than you might expect.

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, together with hundreds of examples, self-assessment tests to consolidate knowledge, and **additional website material** for those wanting to learn more.

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.

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### Supplements

good book but not for undergraduates

**Health and Human Sciences Program, Albany College of Pharmacy and Health Sciences**

Super book, but a bit too much material to serve as a supplement in an undergrad course. I will definitely keep Field's R book in mind for an upper-level R course or graduate data analysis course.

**Statistics, St John Fisher College**

easy to follow. Well structured

**Department of Psychology, City University**

Andy Field is amazing, and I love his books.

**Psychology Dept, The College Of Idaho**

the book is too difficult for our students and the requirements.

**school of health science, nanyang polytechnic**

Covers basic to multivariate statistical analyses with clear and sometimes funny examples. Very useful for postgrad students, and partly for undergrad also.

Introduction to R-statistics is clear and informative. R-statistics is a good option for Master students who are often working on their home computer without access to expensive licensed statistical programmes. I will recommend this book for Master students and use as supplementary book for undergrad students.

**School of Health, Care and Social Welfare, Mälardalen University**

While a well-written and detailed tome, it would be over the heads of my students. If I teach our grad level stats course, I could see using this, though. I have recommended the book to grad students and colleagues, but at this time my undergrads would flee my course en masse if I were to use this. Students with a stronger math, programming or stats background would do well with this book, as they would be less likely to be overwhelmed by the cognitive load presented by the novelty of the statistical concepts and coding by hand (as opposed to using a GUI-enabled statistics program).

**Geography Dept, Brock University**

This text is quite comprehensive; too much so for my students. It would be more appropriate if I were using R for a wider range of courses.

**General Education Prog, Devry University-Addison**