This book is the winner of the 2007 British Psychological Society Award. 'It is noteworthy that after I used some of the illustrations and mentioned the book in class, most students went and bought a copy. Their final papers were heavily 'Field-referenced'! That is the best endorsement one can give to a text' - "Journal of Advanced Nursing". 'The wide range of statistical techniques covered combined with good accompanying background explanations, communicated in a relaxed, affable style, make this book a useful addition to the bookshelves of both practitioners and teachers of statistics alike in the social sciences' - Peter Watson, MRC Cognition and Brain Sciences Unit, Cambridge and Chair of ASSESS, Independent European Group of SPSS Users. 'The Second Edition of Andy Field's "Discovering Statistics Using SPSS" is an excellent book and a valuable addition to the teaching of statistics in the behavioral sciences. The title of the book accurately reflects the approach taken. This is not simply a primer on how to use SPSS, but is a very good statistics text using SPSS as a vehicle for illustrating and expanding on the statistical content of the book. At the same time it also serves as a manual for SPSS, and has taught me things that I had not known about the software. One advantage of the text is that it is not tied specifically to the latest version of SPSS. Although the examples use version 12.0, there are many references to the difference the students will find if they are using an earlier version. A good example of how the text is structured can be seen in Chapters 8 and 9. Chapter 8 provides an introduction to the analysis of variance, and roughly the first 40 pages are devoted to statistical issues. Only after that introduction does the author move to a discussion of using SPSS to run the analyses. Chapter 9 deals with the analysis of covariance, and here the author moves almost immediately to SPSS printout, having laid most of the groundwork in the previous chapter. I find this flexible approach to the blending of content and software to be an effective way of teaching the material. It is impossible to review this book without commenting on Andy's particular style. I enjoyed it immensely and think that it would appeal to both students and their instructors. It is refreshing to see someone who doesn't take himself too seriously' - David C Howell, Professor Emeritus, University of Vermont. 'The new edition of Field's textbook confirms its place as the best statistics text for undergraduate social science students. It provides support for those less confident about statistical analysis whilst having sufficient depth that it will still be valuable to more mathematically experienced people. There is a focus throughout on the practical aspects of data analysis and interpretation whilst at the same time emphasizing the importance of rigour and a good understating of theory! essential reading' - Dr Ian Walker, Department of Psychology, University of Bath. 'Very useful, valuable and interesting. Summing up: Highly recommended' - "Choice", Current Reviews for Academic Librarians. This new edition of Field's textbook provides students of statistical methods with everything they need to understand, use and report statistics - at every level. Written in Andy Field's vivid and entertaining style, and furnished with playful examples from everyday student life (among other places), this book forms an accessible gateway into the often intimidating world of statistics and a unique opportunity for students to ground their knowledge of statistics through the use of SPSS. This text is fully compliant with the latest release of SPSS (version 13). The key updates in the new edition include: more coverage with completely new material on non-parametric statistics, loglinear analysis, effect sizes and how to report statistical analysis; even more student-friendly features, including a glossary of key statistical terms and exercises at the end of chapters for students to work through, with datasets and answers to chapter exercises on the accompanying CD-ROM; and, a larger and more easy-to-reference format: notation in each section identifies the intended level of study while the new 2-colour text design enhances the features in the book and, together with the larger format, provides extra clarity throughout. Andy Field is a Senior Lecturer in Psychology at The University of Sussex where his success in making statistics accessible was recognized with a teaching award in 2001. He is also winner of the British Psychological Society Award for Excellence in the Teaching of Psychology.

Table of Contents:
EVERYTHING YOU WANTED TO KNOW ABOUT STATISTICS (WELL, SORT OF) Building Statistical Models Populations and Samples Simple Statistical Models Frequency Distributions Is My Sample Representative of the Population? Linear Models How Can We Tell If Our Model Represents the Real World? THE SPSS ENVIRONMENT Versions of SPSS Getting Started The Data Editor The Output Viewer The Syntax Window Saving Files Retrieving a File EXPLORING DATA Parametric Data Graphing and Screening Data Exploring Groups of Data Testing Whether a Distribution is Normal Testing for Homogeneity of Variance Graphing Means CORRELATION How Do We Measure Relationships? Data Entry for Correlation Analysis Using SPSS Graphing Relationships The Scatterplot Bivariate Correlation Partial Correlation How To Report Correlation Coefficients REGRESSION An Introduction to Regression Doing Simple Regression on SPSS Interpreting a Simple Regression Multiple Regression The Basics How Accurate Is My Regression Model? How To Do Multiple Regression Using SPSS Interpreting Multiple Regression How To Report Multiple Regression Categorical Predictors and Multiple Regression LOGISTIC REGRESSION Background to Logistic Regression What Are the Principles behind Logistic Regression? Running the Analysis A Research Example Interpreting Logistic Regression How To Report Logistic Regression Another Example Testing for Multicollinearity Things That Can Go Wrong COMPARING TWO MEANS Revision of Experimental Research Inputting Data and Displaying Means with Error Bar Charts Testing Differences between Means The t-Test The Dependent t-Test The Independent t-Test Between Groups or Repeated Measures? The t-Test as a General Linear Model What If Our Data Are Not Normally Distributed? COMPARING SEVERAL MEANS: ANOVA (GLM 1) The Theory behind ANOVA Running One-Way ANOVA on SPSS Output from One-Way ANOVA Calculating the Effect Size Reporting Results from One-Way Independent ANOVA Violations of Assumptions in One-Way Independent ANOVA ANALYSIS OF COVARIANCE, ANCOVA (GLM 2) What Is ANCOVA? Conducting ANCOVA on SPSS Interpreting the Output from ANCOVA ANCOVA Run as a Multiple Regression Additional Assumptions in ANCOVA Calculating the Effect Size Reporting Results FACTORIAL ANOVA (GLM 3) Theory of Factorial ANOVA (Between Groups) Factorial ANOVA Using SPSS Output from Factorial ANOVA Interpreting Interaction Graphs Calculating Effect Sizes Reporting the Results of Two-Way ANOVA Factorial ANOVA as Regression REPEATED-MEASURES DESIGNS (GLM 4) Introduction to Repeated-Measures Designs Theory of One-Way Repeated-Measures ANOVA One-Way Repeated-Measures ANOVA Using SPSS Output for One-Way Repeated-Measures ANOVA Effect Sizes for Repeated-Measures ANOVA Reporting One-Way Repeated-Measures ANOVA Repeated-Measures with Several Independent Variables Output for Factorial Repeated-Measures ANOVA Effect Sizes for Factorial Repeated-Measures ANOVA Reporting the Results from Factorial Repeated-Measures ANOVA MIXED DESIGN ANOVA (GLM 5) Mixed ANOVA on SPSS Output for Mixed Factorial ANOVA Main Analysis Calculating Effect Sizes Reporting the Results of Mixed ANOVA NON-PARAMETRIC TESTS Comparing Two Independent Conditions The Wilcoxon Rank-Sum Test and Mann-Whitney 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 MULTIVARIATE ANALYSIS OF VARIANCE (MANOVA) Introduction Similarities and Differences to ANOVA Theory of MANOVA Assumptions of MANOVA MANOVA on SPSS Output from MANOVA Following Up MANOVA with Discriminant Analysis Output from the Discriminant Analysis EXPLORATORY FACTOR ANALYSIS Factors Discovering Factors Research Example Running the Analysis Interpreting Output from SPSS Reliability Analysis CATEGORICAL DATA Theory of Analyzing Categorical Data Assumptions of the Chi-Square Test Doing Chi-Square on SPSS Several Categorical Variables Log Linear Analysis Assumptions in Loglinear Analysis Loglinear Analysis Using SPSS Output from Loglinear Analysis Following Up Loglinear Analysis Effect Sizes in Loglinear Analysis Reporting the Results of Loglinear Analysis