IBM SPSS for Introductory Statistics Use and Interpretation

Acknowledgements

Preface

1. Variables, Research Problems, and Questions

• Research Problems
• Variables
• Research Hypotheses and Questions
• A Sample Research Problem: The Modified High School and Beyond (HSB) Study
• Levels of Measurement
• Interpretation Questions

2. Getting Data Ready for Analysis and understanding it: Data Collection, Coding, and Description

• Plan the Study, Pilot Test, and Collect Data
• Download Data Collected Online
• Data Coding and Descriptive Analysis
• Problem 2.1: Count Math Courses Taken
• Problem 2.2: Recode and Relabel Mother’s and Father’s Education
• Problem 2.3: Reverse Low Pleasure Items for Pleasure Scale Score
• Problem 2.4: Compute Pleasure Scale with the Mean Function
• Checking for Errors and Normality for the New Variables
• Problem 2.5: Descriptive Statistics for Ordinal and Scale Variables
• Problem 2.6: Boxplots Split by a Dichotomous Variable
• Problem 2.7: Using Tables for Data Description with Dichotomous Variables
• Problem 2.8: Using Frequency Tables for multi-category variables
• Describing the Sample Demographics and Key Variables
• Problem 2.9: Bar Charts
• Interpretation Questions
• Extra SPSS Problems

3. Selecting and Interpreting Inferential Statistics

• General Design Classifications for Difference Questions
• Selection of Inferential Statistics
• The General Linear Model
• Interpreting the Results of a Statistical Test
• An Example of How to Select and Interpret Inferential Statistics
• Writing About Your Outputs
• Conclusion
• Interpretation Questions

4. Methods to Provide Evidence for Reliability and Validity

• Measurement Reliability
• Measurement Validity
• Problem 4.1: Cohen’s Kappa to Assess Reliability with Nominal Data
• Problem 4.2: Correlation and Paired t to Assess Interrater Reliability
• Problem 4.3: Exploratory Factor Analysis to Assess Evidence for Validity
• Problem 4.4: Cronbach’s Alpha to Assess Internal Consistency Reliability
• The Use of Factor Analysis and Alpha to Make Summated Scales
• Interpretation Questions
• Extra SPSS Problems

5. Cross-Tabulation, Chi-Square, and Nonparametric Measures of Association

• Problem 5.1: Chi-Square and Phi (or Cramer’s V)
• Problem 5.2: Risk Ratios and Odds Ratios
• Problem 5.3: Other Nonparametric Associational Statistics
• Problem 5.4: Eta
• Interpretation Questions
• Extra SPSS Problems

6. Correlation and Regression

• Problem 6.1: Scatterplots to Check the Assumption of Linearity
• Problem 6.2: Bivariate Pearson and Spearman Correlations
• Problem 6.3: Correlation Matrix for Several Variables
• Problem 6.4: Bivariate or Simple Linear Regression
• Problem 6.5: Multiple Regression
• Interpretation Questions
• Extra SPSS Problems

7. Comparing Groups with t Tests, Analysis of Variance (ANOVA), and Similar

• Nonparametric Tests
• Problem 7.1: One-Sample t Test
• Problem 7.2: Independent Samples t Test
• Problem 7.3: The Nonparametric Mann–Whitney U Test
• Problem 7.4: Paired Samples t Test
• Problem 7.5: Nonparametric Wilcoxon Test for Two Related Samples
• Problem 7.6: One-Way (or Single Factor) ANOVA
• Problem 7.7: Post Hoc Multiple Comparison Tests
• Problem 7.8: Nonparametric Kruskal–Wallis Test
• Problem 7.9: Two-Way (or Factorial) ANOVA
• Interpretation Questions
• Extra SPSS Problems

Appendices

A. Getting Started and Other Useful SPSS Procedures - Marisha Lamont-Manfre

B. Writing Research Problems and Questions

C. Answers to Odd Numbered Interpretation Questions - Xia Xue

D. Glossary - Jessica Bochert

For Further Reading

Index

Biography

Karen C. Barrett is Professor Emerita of Human Development and Family Studies at Colorado State University, where she taught research methods and statistics classes as well as classes in her research area. She is also Professor of Community & Behavioral Health at Colorado School of Public Health. She received her PhD in developmental psychology from the University of Denver. Her research takes a functional approach to studying emotional and motivational processes and their influence on development; family and cultural influences on emotion regulation; and the development of emotion regulation and social emotions.

Nancy L. Leech is Professor of Research and Evaluation Methods at the University of Colorado, Denver. She teaches graduate level courses in research, statistics, and measurement. She received her PhD in education with an emphasis on research and statistics from Colorado State University in 2002. Her area of research is promoting new developments and better understandings in applied, quantitative, qualitative, and mixed methods research.

Gene W. Gloeckner is Professor Emeritus. He has served as IRB Chair, School of Education Director, and Semester at Sea Dean. He received the Jack E Cermak University Advising Award in 2024. He earned his PhD and BS from The Ohio State University and MS from Colorado State University. Much of his writing and teaching has focused on issues in quantitative and mixed research methods. He has served as the academic advisor for over 75 doctoral graduates. 

George A. Morgan is Emeritus Professor of Education and Human Development at Colorado State University. He received his PhD in child development and psychology from Cornell University. In addition to writing textbooks, he has advised many PhD students in education and related fields. He has conducted a program of research on children’s motivation to master challenging tasks.