SPSS Survival Manual

Julie Pallant has spent the past 25 years helping students overcome ‘statistics phobia’ in her roles as Director of Research and Graduate Studies in the Department of Rural Health at the University of Melbourne, and Senior Lecturer in Applied Statistics at Swinburne University. She has worked as a counselling psychologist and has taught psychology, statistics and research methods at a number of universities. She now works as a research and statistical consultant.

'Julie Pallant has a rare gift for making statistics feel less daunting. This book continues to be my go-to recommendation for researchers new to SPSS – it walks readers through each step in a reassuring, accessible way, making even the most technical concepts feel manageable. The updated edition maintains everything that has made this book a classic, while ensuring alignment with the latest versions of SPSS''.Dr Lyn Lavery, Director, Academic Consulting'An excellent introduction to using SPSS for data analysis. It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided'.Associate Professor George Dunbar, University of Warwick'This book is recommended as ESSENTIAL to all students completing research projects - minor and major'.Dr John Roodenburg, Monash University

• Introduction and overview Part one Getting started 1. Designing a study 2. Preparing a codebook 3. Getting to know IBM SPSS Statistics Part two Preparing the data file 4. Creating a data file and entering data 5. Screening and cleaning the data Part three Preliminary analyses 6. Descriptive statistics 7. Using graphs to describe and explore the data 8. Manipulating the data 9. Checking the reliability of a scale 10. Choosing the right statistic Part four Statistical techniques to explore relationships among variables 11. Correlation 12. Partial correlation 13. Multiple regression 14. Logistic regression 15. Factor analysis Part five Statistical techniques to compare groups 16. Non-parametric statistics 17. T-tests 18. One-way analysis of variance 19. Two-way between-groups ANOVA 20. Mixed between-within subjects analysis of variance 21. Multivariate analysis of variance 22. Analysis of covariance; Glossary of Statistical Terms; Appendix A: Details of data files; Appendix B: Using Syntax