Using IBM SPSS Statistics 3/e

James O. Aldrich (Doctor of Public Administration, University of Laverne) is a retired lecturer on statistics and research methods at California State University, Northridge. He has also taught graduate level research courses for the University of La Verne. Dr. Aldrich held the appointment of Instructor in the Department of Pathology at the University of Southern California, School of Medicine where he served as the Principal Investigator and codirector of a National Cancer Institute research project. He has served on various committees for the Los Angeles chapter of the American Statistical Association and has also taught biostatistics, epidemiology, social statistics, and research methods courses for 20 years. The primary computer program used for his coursework has been the IBM SPSS Statistics software package. SAGE recently published, in 2013, Building SPSS Graphs to Understand Data, coauthored with Hilda M. Rodriguez.

Preface Acknowledgments About the Author SECTION I. SPSS COMMANDS AND ASSIGNMENT OF LEVELS OF MEASUREMENT 1. First Encounters 1.1 Introduction and Objectives 1.2 Entering, Analyzing, and Graphing Data 1.3 Summary 1.4 Review Exercises 2. Navigating in SPSS 2.1 Introduction and Objectives 2.2 SPSS Variable View Screen 2.3 SPSS Data View Screen 2.4 SPSS Main Menu 2.5 Data Editor Toolbar 2.6 Variable View Screen: A Closer Look 2.7 Summary 2.8 Review Exercises 3. Getting Data In and Out of SPSS 3.1 Introduction and Objectives 3.2 Typing Data Using the Computer Keyboard 3.3 Saving Your SPSS Data Files 3.4 Saving Your SPSS Output Files 3.5 Opening Your Saved SPSS Files 3.6 Opening SPSS Sample Files 3.7 Copying and Pasting Data to Other Applications 3.8 Exporting SPSS Files to Other Applications 3.9 Importing Files From Other Applications 3.10 Summary 3.11 Review Exercises 4. Levels of Measurement 4.1 Introduction and Objectives 4.2 Variable View Screen: Measure Column 4.3 Variables Measured at the Nominal Level 4.4 Variables Measured at the Ordinal Level 4.5 Variables Measured at the Scale Level 4.6 Using SPSS to Suggest Variable Measurement Levels 4.7 Summary 4.8 Review Exercises 5. Entering Variables and Data and Validating Data 5.1 Introduction and Objectives 5.2 Entering Variables and Assigning Attributes (Properties) 5.3 Entering Data for Each Variable 5.4 Validating Data for Datasets 5.5 Summary 5.6 Review Exercises 6. Working With Data and Variables 6.1 Introduction and Objectives 6.2 Computing a New Variable 6.3 Recoding Scale Data Into a String Variable 6.4 Data Transformation 6.5 Split Cases for Independent Analysis 6.6 Obtaining a Simple Random Sample (SRS) 6.7 Inserting New Variables and Cases Into Existing Datasets 6.8 Data View Page: Copy, Cut, and Paste Procedures 6.9 Summary 6.10 Review Exercises 7. Printing Data View, Variable View, and Output Viewer Screens 7.1 Introduction and Objectives 7.2 Printing Data From the Variable View Screen 7.3 Printing Variable Information From the Output Viewer 7.4 Printing Tables From the Output Viewer 7.5 Summary 7.6 Review Exercises 8. Using the SPSS Help Menu 8.1 Introduction and Objectives 8.2 Help Options 8.3 Using SPSS Tutorials 8.4 Using SPSS Case Studies 8.5 Using Context Sensitive 8.6 Summary 8.7 Review Exercises SECTION II. DESCRIPTIVE STATISTICS AND GRAPHING 9. Descriptive Statistics 9.1 Introduction and Objectives 9.2 Measures of Central Tendency 9.3 Measures of Dispersion 9.4 The Big Question: Are the Data Normally Distributed? 9.5 Descriptive Statistics for the Class Survey 9.6 Summary 9.7 Review Exercises 10. Creating Graphs for Nominal and/or Ordinal Data 10.1 Introduction and Objectives 10.2 A Brief Introduction to the Chart Builder 10.3 Using the Chart Builder to Build a Simple 3-D Pie Graph 10.4 Building a Population Pyramid 10.5 Building the Stacked Bar Graph (percentage of stack's total) 10.6 Summary 10.7 Review Exercises 11. Creating Graphs for Continuous Data 11.1 Introduction and Objectives 11.2 Creating a Histogram 11.3 Creating a Boxplot 11.4 Creating a Paneled Graph 11.5 Summary 11.6 Review Exercises SECTION III. BASIC INFERENTIAL STATISTICS 12. Inferential Statistics 12.1 Introduction and Objectives 12.2 Populations 12.3 Sampling 12.4 Normal Curve 12.5 Standard Error 12.6 Confidence Intervals 12.7 Hypothesis Testing 12.8 Statistical Significance 12.9 Type I (Alpha) and Type II (Beta) Errors 12.10 Research Steps in Hypothesis Testing 12.11 Parametric Versus Nonparametric Tests 12.12 Practical Versus Statistical Significance 12.13 Summary 12.14 Review Exercises 13. One-Sample t Test and a Binomial Test of Equality 13.1 Introduction and Objectives 13.2 Research Scenario and Test Selection 13.3 Research Question and Null Hypothesis 13.4 Data Input, Analysis, and Interpretation of Output 13.5 Confidence Intervals 13.6 Nonparametric Test: The Binomial Test of Equality 13.7 Summary 13.8 Review Exercises 14. Independent-Samples t Test and the Mann-Whitney U Test 14.1 Introduction and Objectives 14.2 Research Scenario and Test Selection 14.3 Research Question and Null Hypothesis 14.4 Data Input, Analysis, and Interpretation of Output 14.5 Nonparametric Test: Mann-Whitney U Test 14.6 Summary 14.7 Review Exercises 15. Paired-Samples t Test and the Wilcoxon Test 15.1 Introduction and Objectives 15.2 Research Scenario and Test Selection 15.3 Research Question and Null Hypothesis 15.4 Data Input, Analysis, and Interpretation of Output 15.5 Nonparametric Test: Wilcoxon Signed-Ranks Test 15.6 Summary 15.7 Review Exercises 16. One-Way ANOVA and Kruskal-Wallis Test 16.1 Introduction and Objectives 16.2 Research Scenario and Test Selection 16.3 Research Question and Null Hypothesis 16.4 Data Input, Analysis, and Interpretation of Output 16.5 Nonparametric Test: Kruskal-Wallis Test 16.6 Summary 16.7 Review Exercises 17. One-Way ANOVA Repeated Measures Test and Friedman Test 17.1 Introduction and Objectives 17.2 Research Scenario and Test Selection 17.3 Research Question and Null Hypothesis 17.4 Data Input, Analysis, and Interpretation of Output 17.5 Nonparametric Test: Friedman Test 17.6 Summary 17.7 Review Exercises 18. Two-Way ANOVA (Factorial) 18.1 Introduction and Objectives 18.2 Research Scenario and Test Selection 18.3 Research Question and Null Hypothesis 18.4 Data Input, Analysis, and Interpretation of Output 18.5 Summary 18.6 Review Exercises 19. Analysis of Covariance (ANCOVA) 19.1 Introduction and Objectives 19.2 Research Scenario and Test Selection 19.3 Research Question and Null Hypothesis 19.4 Data Input, Analysis, and Interpretation of Output 19.5 Summary 19.6 Review Exercises 20. Chi-Square Goodness of Fit 20.1 Introduction and Objectives 20.2 Research Scenario and Test Selection: Legacy Dialogs 20.3 Research Question and Null Hypothesis: Legacy Dialogs 20.4 Data Input, Analysis, and Interpretation of Output: Legacy Dialogs 20.5 Research Scenario and Test Selection: One Sample 20.6 Research Question and Null Hypothesis: One Sample 20.7 Data Input, Analysis, and Interpretation of Output: One Sample 20.8 Summary 20.9 Review Exercises 21. Chi-Square Test of Independence 21.1 Introduction and Objectives 21.2 Research Scenario and Test Selection: Summarized Data 21.3 Research Question and Null Hypothesis: Summarized Data 21.4 Data Input, Analysis, and Interpretation of Output: Summarized Data 21.5 Research Scenario and Test Selection: Raw Data 21.6 Research Question and Null Hypothesis: Raw Data 21.7 Data Input, Analysis, and Interpretation of Output: Raw Data 21.8 Summary 21.9 Review Exercises SECTION IV. RELATIONAL STATISTICS - PREDICTION, DESCRIBING, AND EXPLORING MULTIVARIABLE RELATIONSHIPS 22. Pearson's and Spearman's Correlation Coefficients 22.1 Introduction and Objectives 22.2 Research Scenario and Test Selection 22.3 Research Question and Null Hypothesis 22.4 Data Input, Analysis, and Interpretation of Output 22.5 Nonparametric Test: Spearman's Correlation Coefficient 22.6 Summary 22.7 Review Exercises 23. Simple Linear Regression 23.1 Introduction and Objectives 23.2 Research Scenario and Test Selection 23.3 Research Question and Null Hypothesis 23.4 Data Input 23.5 Data Assumptions (Normality) 23.6 Data Assumptions (Linear Relationship) 23.7 Regression and Prediction 23.8 Interpretation of Output (Data Assumptions) 23.9 Interpretation of Output (Regression and Prediction) 23.10 Research Question Answered 23.11 Summary 23.12 Review Exercises 24. Multiple Linear Regression 24.1 Introduction and Objectives 24.2 Research Scenario and Test Selection 24.3 Research Question and Null Hypothesis 24.4 Data Input 24.5 Data Assumptions (Normality) 24.6 Regression and Prediction 24.7 Interpretation of Output (Data Assumptions) 24.8 Interpretation of Output (Regression and Prediction) 24.9 Research Question Answered 24.10 Summary 24.11 Review Exercises 25. Logistic Regression 25.1 Introduction and Objectives 25.2 Research Scenario and Test Selection 25.3 Research Question and Null Hypothesis 25.4 Data Input, Analysis, and Interpretation of Output 25.5 Summary 25.6 Review Exercises 26. Factor Analysis 26.1 Introduction and Objectives 26.2 Research Scenario and Test Selection 26.3 Research Question and Null Hypothesis 26.4 Data Input, Analysis, and Interpretation of Output 26.5 Summary 26.6 Review Exercises Appendix A. Class Survey Dataset (Entered in Chapter 5) Appendix B. Normal Curve Interpretation Appendix C. Answers to Review Exercises 1, 2, and 3 Appendix D. Datasets Listed by Chapter Index

"I am very appreciative of the authors' depth and clear writing with comprehensible and useful examples throughout this text." -- Dr. Billy R. Brocato