Introduction to Statistics in Psychology

Introduction to Statistics in Psychology

Paperback

By (author) Dennis Howitt, By (author) Duncan Cramer

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Paperback $114.99
  • Publisher: Prentice-Hall
  • Format: Paperback | 672 pages
  • Dimensions: 196mm x 265mm x 30mm | 1,592g
  • Publication date: 13 January 2011
  • Publication City/Country: Harlow
  • ISBN 10: 027373430X
  • ISBN 13: 9780273734307
  • Edition: 5, Revised
  • Edition statement: 5th Revised edition
  • Sales rank: 85,892

Product description

Introduction to Statistics in Psychology, 5th edition is the comprehensive, straightforward and essential student guide to understanding statistics and carrying out statistical analyses in psychology. Revised and updated throughout, the text offers clear and detailed coverage of the statistical methods used by psychologists.  Key aspects of the process are highlighted throughout the text in special sections: ‘Research Design Issues’  offers advice and guidance on important topics and concepts. ‘Examples from the published literature’ highlight how tests have been applied in interesting classic and more recent research. ‘Calculation’ presents and separates out the mathematical principles underlying the analyses. ‘Quick Steps Guide’ -  this new feature offers a practical, quick guide on how to carry out a statistical analysis in SPSS Statistics and helps students understand the links between the different tests. This book is supported by a companion website featuring a range of resources to help students in their studies.  Self test questions, additional datasets and plus handy quick guides to carrying out tests can all be found at www.pearsoned.co.uk/howitt   "Howitt and Cramer’s “Introduction to Statistics in Psychology” maintains its lead as the best textbook in what is the most difficult area of study for most psychology students. Indeed, it is more than an ‘introduction’ – its’ clear and comprehensive coverage of statistical analysis from basic descriptive and bivariate techniques to multivariate methods will be a priceless resource for students throughout all years of study." Ronnie Wilson, University of Ulster

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Table of contents

Guided tour Introduction List of figures List of tables List of boxes Acknowledgements 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 Scores 5. Standard deviation and z-scores: The standard unit of measurement in statistics 6. Relationships between two or more variables: Diagrams and tables 7. Correlation coefficients: Pearson correlation and Spearman's rho 8. Regression: Prediction with precision Part 2: Significance testing 9. Samples and populations: Generalising and inferring 10. Statistical significance for the correlation coefficient: A practical introduction to statistical inference 11. Standard error: The standard deviation of the means of samples 12. The t-test: Comparing two samples of correlated/related/paired scores 13. The t-test: Comparing two samples of unrelated/uncorrelated scores 14. Chi-square: Differences between samples of frequency data 15. Probability 16. Reporting significance levels succinctly 17. One-tailed versus two-tailed significance testing 18. Ranking tests: Nonparametric statistics Part 3: Introduction to analysis of variance 19. The variance ratio test: The F-ratio to compare two variances 20. Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA 21. Analysis of variance for correlated scores or repeated measures 22. 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 together 25. Analysis of covariance: Controlling for additional variables 26. Multivariate Analysis of Variance (MANOVA) 27. Discriminant (Function) analysis especially in MANOVA 28. Statistics and the analysis of experiments Part 4: More advanced correlational statistics 29. Partial correlation: Spurious correlation, third or confounding variables, suppressor variables 30. Factor analysis: Simplifying complex data 31. Multiple regression and multiple correlation 32. Path analysis 33. The analysis of a questionnaire/survey project Part 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 research 36. Reliability in scales and measurement: Consistency and agreement 37. Confidence intervals 38. The influence of moderator variables on relationships between two variables 39. Statistical power analysis: getting the sample size right Part 6: Advanced qualitative or nominal techniques 40. Log-Linear Methods: The analysis of complex contingency tables 41. Multinomial logistic regression: Distinguishing between several different categories 42. 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