SPSS Survival Manual 4th Edition

Julie Pallant's SPSS Survival Manual throws a lifeline to students and researchers grappling with this data analysis software.

In this thoroughly revised edition of her bestselling text, now covering up to version 18 of the SPSS software, 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 easy to follow 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. In this fourth edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output. A number of additional techniques (McNemar's Test, Cochran's Q Test) have been included in the Non_parametric Statistics chapter. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is THE essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing.

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Julie Pallant has spent many years helping students overcome 'statistics phobia'. She is Director of Research and Graduate Studies in the School of Rural Health at the University of Melbourne. She has worked as a counselling psychologist and has taught psychology, statistics and research methods at a number of universities.

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Preface
Data files and website
Introduction and overview

Part One: Getting started

Designing a study
Preparing a codebook
Getting to know SPSS

Part Two: Preparing the data file

Creating a data file and entering data
Screening and cleaning the data

Part Three: Preliminary analyses

Descriptive statistics
Using graphs to describe and explore the data
Manipulating the data
Checking the reliability of a scale
Choosing the right statistic

Part Four: Statistical techniques to explore relationships among variables

Correlation
Partial correlation
Multiple regression
Logistic regression
Factor analysis

Part Five: Statistical techniques to compare groups

Non-parametric statistics
T-tests
One-way analysis of variance
Two-way between-groups ANOVA
Mixed between-within subjects analysis of variance
Multivariate analysis of variance
Analysis of covariance

Appendix: Details of data files
Recommended reading
References
Index

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