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    Introduction to Statistics in Psychology (Paperback) By (author) Dennis Howitt, By (author) Duncan Cramer

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    DescriptionIntroduction 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.


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    Title
    Introduction to Statistics in Psychology
    Authors and contributors
    By (author) Dennis Howitt, By (author) Duncan Cramer
    Physical properties
    Format: Paperback
    Number of pages: 744
    Width: 194 mm
    Height: 264 mm
    Thickness: 30 mm
    Weight: 1,360 g
    Language
    English
    ISBN
    ISBN 13: 9781292000749
    ISBN 10: 1292000740
    Classifications

    BIC E4L: PSY
    B&T Book Type: NF
    Nielsen BookScan Product Class 3: S2.2T
    B&T Merchandise Category: TXT
    BIC subject category V2: PBT
    LC subject heading:
    LC classification: BF
    B&T General Subject: 670
    BIC subject category V2: JMBT
    Abridged Dewey: 150
    BISAC V2.8: PSY032000, PSY000000
    DC23: 150.15195
    Thema V1.0: PBT, JMBT
    Edition
    6, Revised
    Edition statement
    6th Revised edition
    Publisher
    Pearson Education Limited
    Imprint name
    Pearson Education Limited
    Publication date
    17 March 2014
    Publication City/Country
    Harlow
    Table of contents
    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