Introduction to SPSS in Psychology,
4th edition

By Dennis Howett
October 2008
Prentice Hall
Distrubuted by Trans-Atlantic Publications Inc.
ISBN: 9780132051644
416 pages
$62.50 Paper Original

Introduction to SPSS in Psychology 4/e, makes using SPSS for the analysis of data quick and simple.  This student-friendly text offers the most comprehensive coverage of statistical techniques and how SPSS can handle and manipulate all kinds of data.

The fourth edition provides new and extended coverage of what needs to be known about each statistical and data analysis procedure. The user is given a step-by-step guide through what kinds of data to enter and how; the SPSS steps needed to complete the analysis; and how to understand and write-up the results of the analysis.  In no time, users will gain confidence that they understand a full range of statistical techniques and how to use them in practice.

This book is accompanied by a CD containing datasets, worked examples and exercises to allow practice and revision of techniques covered in the book.




Key Differences between SPSS 16 and earlier versions

Guided tour of the book

Guided tour of the accompanying CD

Part 1 Introduction to SPSS

1. Basics of SPSS data entry and statistical analysis

Part 2 Descriptive statistics

2. Describing variables: Tables and diagrams

3. Describing variables numerically: Averages, variation and spread

4. Shapes of distributions of scores

5. Standard deviation: The standard unit of measurement in statistics

6. Relationships between two or more variables: Diagrams and tables

7. Correlation coefficients: Pearson's correlation and Spearman's rho

8. Regression: Prediction with precision

Part 3 Significance testing and basic inferential tests

9. Standard error

10. The t-test: Comparing two samples of correlated/related scores

11. The t-test: Comparing two groups of unrelated/uncorrelated scores

12. Confidence intervals

13. Chi-square: Differences between samples of frequency data

14. Ranking tests for two groups: Non-parametric statistics

15. Ranking tests for three or more groups: Non-parametric statistics

Part 4 Analysis of variance

16. The variance ratio test: Using the F-ratio to compare two variances

17. Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA

18. Analysis of variance for correlated scores or repeated measures

19. Two-way analysis of variance for unrelated/uncorrelated scores

20. Multiple comparisons in ANOVA

21. Two-way mixed analysis of variance (ANOVA)

22. Analysis of covariance (ANCOVA)

23. Multivariate analysis of variance (MANOVA)

24. Discriminant function analysis (for MANOVA)

Part 5 More advanced correlational statistics

25. Partial correlation

26. Factor analysis

27. Item reliability and inter-rater agreement

28. Stepwise multiple regression

29. Hierarchical multiple regression

Part 6 Advanced qualitative or nominal techniques

30. Log-linear analysis

31. Multinomial logistic regression

32. Binomial logistic regression

Part 7 Data handling procedures

33. Reading ASCII or text files into the Data Editor

34. Missing values

35. Recoding values

36. Computing new variables with no values missing

37. Computing new variables with some values missing  

38. Selecting cases

39. Samples and populations: Generating a random sample

40. Inputting a correlation matrix

41. Checking accuracy of data input

Appendix: Other statistics in SPSS




·  The text features an extended discussion of what each statistical technique involves; when it is used; when it shouldn’t be used; the sorts of data required for the analysis; and common problems that cause users difficulty

·  Explains step by step how to enter, analyse and interpret data using SPSS

·  Gives detail about what to report and how to report it

·  Offers an improved structure to help users navigate the chapters more quickly and effectively

·  Includes new chapters on MANOVA and Discriminant Function Analysis as well as a comprehensive glossary

·  Features examples from many fields of psychology to help users understand the range of applications of statistics in data analysis

· It is accompanied by a CD containing datasets, worked examples and exercises to allow practice and revision of techniques covered in the book


‘A much greater emphasis on simplicity of presentation, explanation and clear step-by-step examples makes this new edition an essential student-friendly resource”

Chad Shepherd, Student, London South Bank University, UK

‘The text is student friendly and utilises real data sets, providing step-by-step illustrations and screenshots. This textbook makes light work of both the basic features and the more advanced elements of SPSS.’

Mary Low, St AndrewsUniversity

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