Introduction to Statistics in Psychology, 6th edition is a comprehensive, modern student guide to understanding and using statistics in psychological research. This edition has been significantly revised to incorporate the essential SPSS steps required for carrying out statistical analysis.
Introduction to Statistics in Psychology is a comprehensive, modern guide to understanding and using statistics in psychological research. This edition has been significantly revised to incorporate the essential SPSS steps you need for carrying out statistical analysis.
1. Why statistics?
Part 1: Descriptive statistics
2. Some basics: Variability and measurement
3. Describing variables: Tables and diagrams
4. Describing variables numerically: Averages, variation and spread
5. Shapes of Distributions of Scores
6. Standard deviation and z-scores: The standard unit of measurement in statistics
7. Relationships between two or more variables: Diagrams and tables
8. Correlation coefficients: Pearson correlation and Spearman's rho
9. Regression: Prediction with precision
Part 2: Significance testing
10. Samples and populations: Generalising and inferring
11. Statistical significance for the correlation coefficient: A practical introduction to statistical inference
12. Standard error: The standard deviation of the means of samples
13. The t-test: Comparing two samples of correlated/related scores
14. The t-test: Comparing two samples of unrelated/uncorrelated scores
15. Chi-square: Differences between samples of frequency data
16. Probability
17. Reporting significance levels succinctly
18. One-tailed versus two-tailed significance testing
19. Ranking tests: Nonparametric statistics
Part 3: Introduction to analysis of variance
20. The variance ratio test: The F-ratio to compare two variances
21. Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA
22. Analysis of variance for correlated scores or repeated measures
23. Two-way analysis of variance for unrelated/uncorrelated scores: Two studies for the price of one?
24. Multiple comparisons in ANOVA: Just where do the differences lie?
25. Mixed-design ANOVA: Related and unrelated variables together
26. Analysis of covariance (ANCOVA): Controlling for additional variables
27. Multivariate Analysis of Variance (MANOVA)
28. Discriminant (Function) analysis especially in MANOVA
29. Statistics and the analysis of experiments
Part 4: More advanced correlational statistics
30. Partial correlation: Spurious correlation, third or confounding variables, suppressor variables
31. Factor analysis: Simplifying complex data
32. Multiple regression and multiple correlation
33. Path analysis
34. The analysis of a questionnaire/survey project
Part 5: Assorted advanced techniques
35. The size of effects in statistical analysis: Do my findings matter?
36. Meta-analysis: Combining and exploring statistical findings from previous research
37. Reliability in scales and measurement: Consistency and agreement
38. Confidence intervals
39. The influence of moderator variables on relationships between two variables
40. Statistical power analysis: getting the sample size right
Part 6: Advanced qualitative or nominal techniques
41. Log-Linear Methods: The analysis of complex contingency tables
42. Multinomial logistic regression: Distinguishing between several different categories or groups
43. Binomial Logistic Regression
Appendices
Appendix A: Testing for excessively skewed distributions
Appendix B1: Large sample formulae for the nonparametric tests
Appendix B2: Nonparametric tests for three or more groups
Appendix C: Extended table of significance for the Pearson correlation coefficient
Appendix D: Table of significance for the Spearman correlation coefficient
Appendix E: Extended table of significance for the t-test
Appendix F: Table of significance for Chi-square
Appendix G: Extended table of significance for the sign test
Appendix H: Table of significance for the Wilcoxon Matched Pairs Test
Appendix I: Table of significance for the Mann-Whitney U-test
Appendix J: Table of significance values for the F-distribution
Appendix K: Table of significant values oft when making multiple t-tests
Glossary
References
Index