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Discovering Statistics Using R
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Discovering Statistics Using R

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March 2012 | 992 pages | SAGE Publications Ltd
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.

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.

 
Why Is My Evil Lecturer Forcing Me to Learn Statistics?
What will this chapter tell me?

 
What the hell am I doing here? I don't belong here

 
Initial observation: finding something that needs explaining

 
Generating theories and testing them

 
Data collection 1: what to measure

 
Data collection 2: how to measure

 
Analysing data

 
What have I discovered about statistics?

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Everything You Ever Wanted to Know About Statistics (Well, Sort of)
What will this chapter tell me?

 
Building statistical models

 
Populations and samples

 
Simple statistical models

 
Going beyond the data

 
Using statistical models to test research questions

 
What have I discovered about statistics?

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
The R Environment
What will this chapter tell me?

 
Before you start

 
Getting started

 
Using R

 
Getting data into R

 
Entering data with R Commander

 
Using other software to enter and edit data

 
Saving Data

 
Manipulating Data

 
What have I discovered about statistics?

 
R Packages Used in This Chapter

 
R Functions Used in This Chapter

 
Key terms that I've discovered

 
Smart Alex's Tasks

 
Further reading

 
 
Exploring Data with Graphs
What will this chapter tell me?

 
The art of presenting data

 
Packages used in this chapter

 
Introducing ggplot2

 
Graphing relationships: the scatterplot

 
Histograms: a good way to spot obvious problems

 
Boxplots (box-whisker diagrams)

 
Density plots

 
Graphing means

 
Themes and options

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Exploring Assumptions
What will this chapter tell me?

 
What are assumptions?

 
Assumptions of parametric data

 
Packages used in this chapter

 
The assumption of normality

 
Testing whether a distribution is normal

 
Testing for homogeneity of variance

 
Correcting problems in the data

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
 
Correlation
What will this chapter tell me?

 
Looking at relationships

 
How do we measure relationships?

 
Data entry for correlation analysis

 
Bivariate correlation

 
Partial correlation

 
Comparing correlations

 
Calculating the effect size

 
How to report correlation coefficents

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
 
Regression
What will this chapter tell me?

 
An Introduction to regression

 
Packages used in this chapter

 
General procedure for regression in R

 
Interpreting a simple regression

 
Multiple regression: the basics

 
How accurate is my regression model?

 
How to do multiple regression using R Commander and R

 
Testing the accuracy of your regression model

 
Robust regression: bootstrapping

 
How to report multiple regression

 
Categorical predictors and multiple regression

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Logistic Regression
What will this chapter tell me?

 
Background to logistic regression

 
What are the principles behind logistic regression?

 
Assumptions and things that can go wrong

 
Packages used in this chapter

 
Binary logistic regression: an example that will make you feel eel

 
How to report logistic regression

 
Testing assumptions: another example

 
Predicting several categories: multinomial logistic regression

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Comparing Two Means
What will this chapter tell me?

 
Packages used in this chapter

 
Looking at differences

 
The t-test

 
The independent t-test

 
The dependent t-test

 
Between groups or repeated measures?

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Comparing Several Means: ANOVA (GLM 1)
What will this chapter tell me?

 
The theory behind ANOVA

 
Assumptions of ANOVA

 
Planned contrasts

 
Post hoc procedures

 
One-way ANOVA using R

 
Calculating the effect size

 
Reporting results from one-way independent ANOVA

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Analysis of Covariance, ANCOVA (GLM 2)
What will this chapter tell me?

 
What is ANCOVA?

 
Assumptions and issues in ANCOVA

 
ANCOVA using R

 
Robust ANCOVA

 
Calculating the effect size

 
Reporting results

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Factorial ANOVA (GLM 3)
What will this chapter tell me?

 
Theory of factorial ANOVA (independant design)

 
Factorial ANOVA as regression

 
Two-Way ANOVA: Behind the scenes

 
Factorial ANOVA using R

 
Interpreting interaction graphs

 
Robust factorial ANOVA

 
Calculating effect sizes

 
Reporting the results of two-way ANOVA

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Repeated-Measures Designs (GLM 4)
What will this chapter tell me?

 
Introduction to repeated-measures designs

 
Theory of one-way repeated-measures ANOVA

 
One-way repeated measures designs using R

 
Effect sizes for repeated measures designs

 
Reporting one-way repeated measures designs

 
Factorisal repeated measures designs

 
Effect Sizes for factorial repeated measures designs

 
Reporting the results from factorial repeated measures designs

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Mixed Designs (GLM 5)
What will this chapter tell me?

 
Mixed designs

 
What do men and women look for in a partner?

 
Entering and exploring your data

 
Mixed ANOVA

 
Mixed designs as a GLM

 
Calculating effect sizes

 
Reporting the results of mixed ANOVA

 
Robust analysis for mixed designs

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Non-Parametric Tests
What will this chapter tell me?

 
When to use non-parametric tests

 
Packages used in this chapter

 
Comparing two independent conditions: the Wilcoxon rank-sum test

 
Comparing two related conditions: the Wilcoxon signed-rank test

 
Differences between several independent groups: the Kruskal-Wallis test

 
Differences between several related groups: Friedman's ANOVA

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Multivariate Analysis of Variance (MANOVA)
What will this chapter tell me?

 
When to use MANOVA

 
Introduction: similarities and differences to ANOVA

 
Theory of MANOVA

 
Practical issues when conducting MANOVA

 
MANOVA using R

 
Robust MANOVA

 
Reporting results from MANOVA

 
Following up MANOVA with discriminant analysis

 
Reporting results from discriminant analysis

 
Some final remarks

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Exploratory Factor Analysis
What will this chapter tell me?

 
When to use factor analysis

 
Factors

 
Research example

 
Running the analysis with R Commander

 
Running the analysis with R

 
Factor scores

 
How to report factor analysis

 
Reliability analysis

 
Reporting reliability analysis

 
What have I discovered about statistics?

 
R Packages Used in This Chapter

 
R Functions Used in This Chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Categorical Data
What will this chapter tell me?

 
Packages used in this chapter

 
Analysing categorical data

 
Theory of Analysing Categorical Data

 
Assumptions of the chi-square test

 
Doing the chi-square test using R

 
Several categorical variables: loglinear analysis

 
Assumptions in loglinear analysis

 
Loglinear analysis using R

 
Following up loglinear analysis

 
Effect sizes in loglinear analysis

 
Reporting the results of loglinear analysis

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Multilevel Linear Models
What will this chapter tell me?

 
Hierarchical data

 
Theory of multilevel linear models

 
The multilevel model

 
Some practical issues

 
Multilevel modelling on R

 
Growth models

 
How to report a multilevel model

 
What have I discovered about statistics?

 
R packages used in this chapter

 
R functions used in this chapter

 
Key terms that I've discovered

 
Smart Alex's tasks

 
Further reading

 
Interesting real research

 
 
Epilogue: Life After Discovering Statistics
 
Troubleshooting R
 
Glossary
Appendix

 
Table of the standard normal distribution

 
Critical Values of the t-Distribution

 
Critical Values of the F-Distribution

 
Critical Values of the chi-square Distribution

 
 
References

Supplements

Click for online resources

Companion Website to accompany Discovering Statistics Using R

great intro

Myles Gartland
Management Dept, Rockhurst University
December 30, 2014

good book but not for undergraduates

Dr Tuo Yu Chen
Health and Human Sciences Program, Albany College of Pharmacy and Health Sciences
October 22, 2014

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.

Dr Bruce Blaine
Statistics, St John Fisher College
October 14, 2014

easy to follow. Well structured

Anke Plagnol
Department of Psychology, City University
September 25, 2014

Andy Field is amazing, and I love his books.

Dr Cara Laney
Psychology Dept, The College Of Idaho
September 18, 2014

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

Mr Trina Tan
school of health science, nanyang polytechnic
September 3, 2014

Department recommended.

Professor Marvin McNeese
Political Science Dept, Rice University
August 23, 2014

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.

Ms Maria Sandborgh
School of Health, Care and Social Welfare, Mälardalen University
August 13, 2014

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).

Jeff Boggs
Geography Dept, Brock University
May 22, 2014

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.

Mr Todd Mattson
General Education Prog, Devry University-Addison
April 3, 2014

Sample Materials & Chapters

Chapter One


Andy Field

Andy Field is Professor of Quantitative Methods at the University of Sussex. He has published widely (100+ research papers, 29 book chapters, and 17 books in various editions) in the areas of child anxiety and psychological methods and statistics. His current research interests focus on barriers to learning mathematics and statistics.He is internationally known as a statistics educator. He has written several widely used statistics textbooks including Discovering Statistics Using IBM SPSS Statistics (winner of the 2007 British Psychological Society book award), Discovering Statistics Using R, and An Adventure... More About Author

Jeremy Miles

Jeremy Miles, RAND Corporation, USA. More About Author

Zoe Field

Zoë Field, University of Sussex, UK More About Author