IBM SPSS Statistics 25 Step by Step: A Simple Guide and Reference, fifteenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS.
This book covers both the basics of descriptive statistical analysis using SPSS through to more advanced topics such as multiple regression, multidimensional scaling and MANOVA, including instructions for Windows and Mac. This makes it ideal for both undergraduate statistics courses and for postgraduates looking to further develop their statistics and SPSS knowledge.
New to this edition:
- Updated throughout to SPSS 25
- Updated / restructured material on: Chart Builder; Univariate ANOVA; moderation on two- and three-way ANOVA; and Factor Analytic Techniques (formerly Factor Analysis structure)
- New material on computing z and T scores, and on computing z scores within descriptive statistics
- Clearer in-chapter links between the type of data and type of research question that the procedure can answer
- Updated / additional datasets, exercises, and expanded Companion Website material, including Powerpoint slides for instructors
Table of Contents
1. An Overview of IBM SPSS Statistics
2a. IBM SPSS Statistics Processes for PC
2b. IBM SPSS Statistics Processes for Mac
3. Creating and Editing a Data File
4. Managing Data
5. Graphs and Charts: Creating and Editing
7. Descriptive Statistics
8. Crosstabulation and χ2 Analyses
9. The Means Procedure
10. Bivariate Correlation
11. The t Test Procedure
12. The One-Way ANOVA Procedure
13. General Linear Models: Two-Way ANOVA
14. General Linear Models: Three-Way ANOVA
15. Simple Linear Regression
16. Multiple Regression Analysis
17. Nonparametric Procedures
18. Reliability Analysis
19. Multidimensional Scaling
20. Factor Analysis
21. Cluster Analysis
22. Discriminant Analysis
23. General Linear Models: MANOVA and MANCOVA
24. G.L.M.: Repeated-Measures MANOVA
25. Logistic Regression
26. Hierarchical Log-Linear Models
27. Nonhierarchical Log-Linear Models
28. Residuals: Analyzing Left-Over Variance
Darren George is a Professor of Psychology at Burman University (Alberta, Canada) whose research focuses on intimate relationships. He teaches classes in Personality and Social Psychology, research methods, and multivariate analysis.
Paul Mallery is a Professor of Psychology at La Sierra University whose research focuses on the intersection of religion and prejudice. He teaches classes in research methodology, statistics, social psychology, and political psychology.
Please visit our companion website for additional support materials.