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The internationally successful, user-friendly guide that takes students and researchers through the often daunting process of analysing research data with the widely used SPSS software package. Fully revised and updated for IBM SPSS Statistics version 26.

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About the Book

The internationally successful, user-friendly guide that takes students and researchers through the often daunting process of analysing research data with the widely used SPSS software package. Fully revised and updated for IBM SPSS Statistics version 26.

The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software.

In her bestselling guide, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report.

For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manualis an essential text. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing.

This seventh edition is fully revised and updated to accommodate changes to IBM SPSS Statistics procedures, screens and outputs.

Table of Contents

Preface
Data files and website
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

Appendix: Details of data files
Recommended reading
References
Index

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About the Author

JULIE PALLANT has spent many 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 internationally.