Introduction
Acknowledgements
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
Glossary
Index