Foolproof Guide to Statistics Using IBM SPSS + Experimental Design & Analysis 100013 (Custom Edition), 2nd edition

Published by Pearson (December 9, 2013) © 2014

  • Adelma Hills

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ISBN-13: 9781486024957
Foolproof Guide to Statistics Using IBM SPSS + Experimental Design & Analysis 100013 (Custom Edition)
Published 2013

This custom edition is published for the University of Western Sydney.

Foolproof Guide to Statistics Using IBM SPSS

The name SPSS is used throughout this edition which is intended to provide a foundation for understanding statistics and the use of SPSS. It has been developed primarily for students of psychology, but has application to other disciplines where quantitative research is used (provided the reader can stand having examples drawn from psychology).

New in this edition:

  • How to boxes for SPSS procedures, updated for PASW 18
  • A List of How To Boxes following the Table of Contents
  • The new style for nonparametric tests shown in Appendix 2
  • Sample Results sections updated consistent with the new edition of the APA Manual1
  • A new section on overlapping confidence intervals and statistical significance (p. 141)

Each chapter contains a worked example, and students are advised to treat these as tutorial exercises, working through each one, exploring the other options available in each of the SPSS procedures, examining the output that is produced, and comparing it to the extracts provided in the chapter.

The shaded How to boxes show the steps needed to perform various operations and analyses, and pages illustrating output from analyses are identified by shaded bars down the outside margin.

Experimental Design and Analysis

This edition is compilation of chapters from The Psychologist as Detective: An Introduction to Conducting Research in Psychology.

Foolproof Guide to Statistics Using IBM SPSS
  • 1. Introduction
  • 2. Entering and Saving Data in SPSS
  • 3. The Problem of Variability: Descriptive Statistics for Central Tendency and Variance
  • 4. The Problem of Probability: Frequency Distributions, The Normal Distribution, and Standard Scores
  • 5. The Logic of Significance Testing: One- and Two-Sample z Tests
  • 6. Preparing for Analysis: Data Screening for Parametric Statistics
  • 7. The One-Sample t Test
  • 8. The Dependent-Samples t Test, and Wilcoxon Signed-Rank T Test Nonparametric Alternative
  • 9. The Independent-Samples t Test, and the Mann-Whitney U Test Nonparametric Alternative
  • 10. One-Way Analysis of Variance (ANOVA), and the Kruskal-Wallis Nonparametric Alternative
  • 11. One-Way Repeated Measures ANOVA, and Friedman Alternative
  • 12. Factorial Between-Groups ANOVA
  • 13. ANOVA Alternatives: Planned Comparisons, and Trend Analysis
  • 14. Factorial and Mixed Repeated Measures ANOVA
  • 15. Analysis of Covariance (ANCOVA)
  • 16. Multivariate Analysis of Variance (MANOVA)
  • 17. Discriminant Function Analysis
  • 18. Bivariate Correlation
  • 19. Bivariate Regression
  • 20. Multiple Regression
  • 21. Reliability Analysis
  • 22. Exploratory Factor Analysis
  • 23. Chi-Square
  • 24. Multiway Frequency Analysis (Loglinear Analysis)
  • Appendix 1: The new style for nonparametric tests
  • Appendix 2: New and old ways to create graphs
  • References
  • Index
  • List of Main Statistical Symbols

Experimental Design and Analysis

The custom edition is compiled from the following chapters from The Psychologist as Detective: An Introduction to Conducting Research in Psychology.

  • Chapter 5 Using the Scientific Method in Psychology
  • Chapter 6 Conducting a Good Experiment I: Variables and Control
  • Chapter 7 Conducting a Good Experiment II: Final Considerations, Unanticipated Influences, and Cross-Cultural Issues
  • Chapter 8 Internal and External Validity
  • Chapter 9 Using Statistics to Answer Questions
  • Chapter 10 Designing, Conducting, Analyzing, and Interpreting
  • Chapter 11 Designing, Conducting, Analyzing, and Interpreting
  • Appendix A: Statistical Tables
  • Appendix B: Selected Statistical Formulae
  • Appendix C: Factorial Design with Three Independent Variables
  • Appendix D: Check Your Progress Answers

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