Darren George, Paul Mallery

IBM SPSS Statistics 29 Step by Step

A Simple Guide and Reference

• Broschiertes Buch

Produktbeschreibung

IBM SPSS Statistics 29 Step by Step: A Simple Guide and Reference, eighteenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike.

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Produktdetails

• Verlag: Taylor & Francis Ltd
• 18 ed
• Seitenzahl: 426
• Erscheinungstermin: 29. März 2024
• Englisch
• Abmessung: 276mm x 208mm x 21mm
• Gewicht: 1318g
• ISBN-13: 9781032621937
• ISBN-10: 1032621931
• Artikelnr.: 69482026

Autorenporträt

Darren George teaches at the University of Alabama. His research focuses on intimate relationships and optimal performance. He teaches classes in research methodology, statistics, personality/social psychology, and sport and performance psychology. 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.

Inhaltsangabe

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 6.
Frequencies 7. Descriptive Statistics 8. Crosstabulation and ¿2 Analyses 9.
The Means Procedure 10. A Priori Power Analysis: What Sample Size Do I
Need? 11. Bivariate Correlation 12. The t Test Procedure 13. The One-Way
ANOVA Procedure 14. General Linear Model: Two-Way ANOVA 15. General Linear
Model: Three-Way ANOVA 16. Simple Linear Regression 17. Multiple Regression
Analysis 18. Nonparametric Procedures 19. Reliability Analysis 20.
Multidimensional Scaling 21. Factor Analysis 22. Cluster Analysis 23.
Discriminant Analysis 24. General Linear Models: MANOVA and MANCOVA 25.
G.L.M.: Repeated-Measures MANOVA 26. Logistic Regression 27. Hierarchical
Log-Linear Models 28. Nonhierarchical Log-Linear Models 29. Residuals:
Analyzing Left-Over Variance 30. Meta-Analysis