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Introduction to Statistics in Psychology
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Guided tourIntroductionList of figuresList of tablesList of boxesAcknowledgements Part 1: Descriptive statistics 1. Why you need statistics: Types of data 2. Describing variables: Tables and diagrams 3. Describing variables numerically: Averages, variation and spread 4. Shapes of Distributions of Scores5. Standard deviation and z-scores: The standard unit of measurement in statistics6. Relationships between two or more variables: Diagrams and tables7. Correlation coefficients: Pearson correlation and Spearman's rho8. Regression: Prediction with precisionPart 2: Significance testing 9. Samples and populations: Generalising and inferring10. Statistical significance for the correlation coefficient: A practical introduction to statistical inference11. Standard error: The standard deviation of the means of samples12. The t-test: Comparing two samples of correlated/related/paired scores13. The t-test: Comparing two samples of unrelated/uncorrelated scores14. Chi-square: Differences between samples of frequency data15. Probability16. Reporting significance levels succinctly17. One-tailed versus two-tailed significance testing18. Ranking tests: Nonparametric statisticsPart 3: Introduction to analysis of variance 19. The variance ratio test: The F-ratio to compare two variances20. Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA21. Analysis of variance for correlated scores or repeated measures22. Two-way analysis of variance for unrelated/uncorrelated scores: Two studies for the price of one? 23. Multiple comparisons in ANOVA: Just where do the differences lie?24. Mixed-design ANOVA: Related and Unrelated Variables together25. Analysis of covariance: Controlling for additional variables26. Multivariate Analysis of Variance (MANOVA)27. Discriminant (Function) analysis especially in MANOVA28. Statistics and the analysis of experimentsPart 4: More advanced correlational statistics 29. Partial correlation: Spurious correlation, third or confounding variables, suppressor variables 30. Factor analysis: Simplifying complex data31. Multiple regression and multiple correlation32. Path analysis33. The analysis of a questionnaire/survey projectPart 5: Assorted advanced techniques 34. The size of effects in statistical analysis: Do my findings matter?35. Meta-analysis: Combining and exploring statistical findings from previous research36. Reliability in scales and measurement: Consistency and agreement37. Confidence intervals38. The influence of moderator variables on relationships between two variables39. Statistical power analysis: getting the sample size rightPart 6: Advanced qualitative or nominal techniques40. Log-Linear Methods: The analysis of complex contingency tables41. Multinomial logistic regression: Distinguishing between several different categories 42. Binomial Logistic Regression AppendicesAppendix A: Testing for excessively skewed distributionsAppendix B1: Large sample formulae for the nonparametric testsAppendix B2: Nonparametric tests for three or more groupsAppendix C: Extended table of significance for the Pearson correlation coefficientAppendix D: Table of significance for the Spearman correlation coefficientAppendix E: Extended table of significance for the t-testAppendix F: Table of significance for Chi-squareAppendix G: Extended table of significance for the sign testAppendix H: Table of significance for the Wilcoxon Matched Pairs TestAppendix I: Table of significance for the Mann-Whitney U-testAppendix J: Table of significance values for the F-distributionAppendix K: Table of significant values oft when making multiple t-testsGlossaryReferencesIndex