Description
Book SynopsisResearch Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project, giving advice on planning and conducting studies, analysing data and writing up reports, both quantitative and qualitative. It incorporates diversity and includes a large section on cross-cultural psychology methods and issues.
The book continues its long tradition of integrating qualitative issues into methods chapters as well as providing two chapters dedicated to qualitative methods. It provides clear coverage of experimental, interviewing and observational methods; psychological testing; and statistical procedures which include nominal-level tests, ordinal and interval two-condition tests, simple and multi-factorial ANOVA designs, correlation, multiple regression, log line
Table of Contents
Preface, Acknowledgements, Part 1. Research methods and ethics, 1. Psychology, science and research, 2. Measuring people – variables, samples and the qualitative critique, 3. Experiments and experimental designs in psychology, 4. Validity in psychological research, 5. Quasi-experiments and non-experiments, 6. Observational methods – watching and being with people, 7. Interview methods – asking people direct questions, 8. Psychological tests and measurement scales, 9. Comparison studies – cross-sectional, longitudinal and cross-cultural studies, 10. Qualitative approaches in psychology, 11. Ethical issues in psychological research, Part 2. Analysing data and writing reports, 12. Analysing qualitative data, 13. Statistics – organising the data, 14. Graphical representation of data, 15. Frequencies and distributions, 16. Significance testing – was it a real effect?, 17. Testing for differences between two samples, 18. Tests for categorical variables and frequency tables, 19. Correlation, 20. Regression methods, 21. Factor analysis, 22. Multi-level analysis – differences between more than two conditions (ANOVA), 23. Multi-factorial ANOVA designs, 24. ANOVA for repeated measures designs, 25. Choosing a significance test for your data, 26. Planning your practical and writing up your report, Appendix, References, Index
