Using IBM SPSS Statistics

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.

• PrefaceAcknowledgmentsAbout the AuthorSECTION I. SPSS COMMANDS AND ASSIGNMENT OF LEVELS OF MEASUREMENT1. First Encounters1.1 Introduction and Objectives1.2 Entering, Analyzing, and Graphing Data1.3 Summary1.4 Review Exercises2. Navigating in SPSS2.1 Introduction and Objectives2.2 SPSS Variable View Screen2.3 SPSS Data View Screen2.4 SPSS Main Menu2.5 Data Editor Toolbar2.6 Variable View Screen: A Closer Look2.7 Summary2.8 Review Exercises3. Getting Data In and Out of SPSS3.1 Introduction and Objectives3.2 Typing Data Using the Computer Keyboard3.3 Saving Your SPSS Data Files3.4 Saving Your SPSS Output Files3.5 Opening Your Saved SPSS Files3.6 Opening SPSS Sample Files3.7 Copying and Pasting Data to Other Applications3.8 Exporting SPSS Files to Other Applications3.9 Importing Files From Other Applications3.10 Summary3.11 Review Exercises4. Levels of Measurement4.1 Introduction and Objectives4.2 Variable View Screen: Measure Column4.3 Variables Measured at the Nominal Level4.4 Variables Measured at the Ordinal Level4.5 Variables Measured at the Scale Level4.6 Using SPSS to Suggest Variable Measurement Levels4.7 Summary4.8 Review Exercises5. Entering Variables and Data and Validating Data5.1 Introduction and Objectives5.2 Entering Variables and Assigning Attributes (Properties)5.3 Entering Data for Each Variable5.4 Validating Data for Datasets5.5 Summary5.6 Review Exercises6. Working With Data and Variables6.1 Introduction and Objectives6.2 Computing a New Variable6.3 Recoding Scale Data Into a String Variable6.4 Data Transformation6.5 Split Cases for Independent Analysis6.6 Obtaining a Simple Random Sample (SRS)6.7 Inserting New Variables and Cases Into Existing Datasets6.8 Data View Page: Copy, Cut, and Paste Procedures6.9 Summary6.10 Review Exercises7. Printing Data View, Variable View, and Output Viewer Screens7.1 Introduction and Objectives7.2 Printing Data From the Variable View Screen7.3 Printing Variable Information From the Output Viewer7.4 Printing Tables From the Output Viewer7.5 Summary7.6 Review Exercises8. Using the SPSS Help Menu8.1 Introduction and Objectives8.2 Help Options8.3 Using SPSS Tutorials8.4 Using SPSS Case Studies8.5 Using Context Sensitive8.6 Summary8.7 Review ExercisesSECTION II. DESCRIPTIVE STATISTICS AND GRAPHING9. Descriptive Statistics9.1 Introduction and Objectives9.2 Measures of Central Tendency9.3 Measures of Dispersion9.4 The Big Question: Are the Data Normally Distributed?9.5 Descriptive Statistics for the Class Survey9.6 Summary9.7 Review Exercises10. Creating Graphs for Nominal and/or Ordinal Data10.1 Introduction and Objectives10.2 A Brief Introduction to the Chart Builder10.3 Using the Chart Builder to Build a Simple 3-D Pie Graph10.4 Building a Population Pyramid10.5 Building the Stacked Bar Graph (percentage of stack’s total)10.6 Summary10.7 Review Exercises11. Creating Graphs for Continuous Data11.1 Introduction and Objectives11.2 Creating a Histogram11.3 Creating a Boxplot11.4 Creating a Paneled Graph11.5 Summary11.6 Review ExercisesSECTION III. BASIC INFERENTIAL STATISTICS12. Inferential Statistics12.1 Introduction and Objectives12.2 Populations12.3 Sampling12.4 Normal Curve12.5 Standard Error12.6 Confidence Intervals12.7 Hypothesis Testing12.8 Statistical Significance12.9 Type I (Alpha) and Type II (Beta) Errors12.10 Research Steps in Hypothesis Testing12.11 Parametric Versus Nonparametric Tests12.12 Practical Versus Statistical Significance12.13 Summary12.14 Review Exercises13. One-Sample t Test and a Binomial Test of Equality13.1 Introduction and Objectives13.2 Research Scenario and Test Selection13.3 Research Question and Null Hypothesis13.4 Data Input, Analysis, and Interpretation of Output13.5 Confidence Intervals13.6 Nonparametric Test: The Binomial Test of Equality13.7 Summary13.8 Review Exercises14. Independent-Samples t Test and the Mann–Whitney U Test14.1 Introduction and Objectives14.2 Research Scenario and Test Selection14.3 Research Question and Null Hypothesis14.4 Data Input, Analysis, and Interpretation of Output14.5 Nonparametric Test: Mann–Whitney U Test14.6 Summary14.7 Review Exercises15. Paired-Samples t Test and the Wilcoxon Test15.1 Introduction and Objectives15.2 Research Scenario and Test Selection15.3 Research Question and Null Hypothesis15.4 Data Input, Analysis, and Interpretation of Output15.5 Nonparametric Test: Wilcoxon Signed-Ranks Test15.6 Summary15.7 Review Exercises16. One-Way ANOVA and Kruskal–Wallis Test16.1 Introduction and Objectives16.2 Research Scenario and Test Selection16.3 Research Question and Null Hypothesis16.4 Data Input, Analysis, and Interpretation of Output16.5 Nonparametric Test: Kruskal–Wallis Test16.6 Summary16.7 Review Exercises17. One-Way ANOVA Repeated Measures Test and Friedman Test17.1 Introduction and Objectives17.2 Research Scenario and Test Selection17.3 Research Question and Null Hypothesis17.4 Data Input, Analysis, and Interpretation of Output17.5 Nonparametric Test: Friedman Test17.6 Summary17.7 Review Exercises18. Two-Way ANOVA (Factorial)18.1 Introduction and Objectives18.2 Research Scenario and Test Selection18.3 Research Question and Null Hypothesis18.4 Data Input, Analysis, and Interpretation of Output18.5 Summary18.6 Review Exercises19. Analysis of Covariance (ANCOVA)19.1 Introduction and Objectives19.2 Research Scenario and Test Selection19.3 Research Question and Null Hypothesis19.4 Data Input, Analysis, and Interpretation of Output19.5 Summary19.6 Review Exercises20. Chi-Square Goodness of Fit20.1 Introduction and Objectives20.2 Research Scenario and Test Selection: Legacy Dialogs20.3 Research Question and Null Hypothesis: Legacy Dialogs20.4 Data Input, Analysis, and Interpretation of Output: Legacy Dialogs20.5 Research Scenario and Test Selection: One Sample20.6 Research Question and Null Hypothesis: One Sample20.7 Data Input, Analysis, and Interpretation of Output: One Sample20.8 Summary20.9 Review Exercises21. Chi-Square Test of Independence21.1 Introduction and Objectives21.2 Research Scenario and Test Selection: Summarized Data21.3 Research Question and Null Hypothesis: Summarized Data21.4 Data Input, Analysis, and Interpretation of Output: Summarized Data21.5 Research Scenario and Test Selection: Raw Data21.6 Research Question and Null Hypothesis: Raw Data21.7 Data Input, Analysis, and Interpretation of Output: Raw Data21.8 Summary21.9 Review ExercisesSECTION IV. RELATIONAL STATISTICS – PREDICTION, DESCRIBING, AND EXPLORING MULTIVARIABLE RELATIONSHIPS22. Pearson’s and Spearman’s Correlation Coefficients22.1 Introduction and Objectives22.2 Research Scenario and Test Selection22.3 Research Question and Null Hypothesis22.4 Data Input, Analysis, and Interpretation of Output22.5 Nonparametric Test: Spearman’s Correlation Coefficient22.6 Summary22.7 Review Exercises23. Simple Linear Regression23.1 Introduction and Objectives23.2 Research Scenario and Test Selection23.3 Research Question and Null Hypothesis23.4 Data Input23.5 Data Assumptions (Normality)23.6 Data Assumptions (Linear Relationship)23.7 Regression and Prediction23.8 Interpretation of Output (Data Assumptions)23.9 Interpretation of Output (Regression and Prediction)23.10 Research Question Answered23.11 Summary23.12 Review Exercises24. Multiple Linear Regression24.1 Introduction and Objectives24.2 Research Scenario and Test Selection24.3 Research Question and Null Hypothesis24.4 Data Input24.5 Data Assumptions (Normality)24.6 Regression and Prediction24.7 Interpretation of Output (Data Assumptions)24.8 Interpretation of Output (Regression and Prediction)24.9 Research Question Answered24.10 Summary24.11 Review Exercises25. Logistic Regression25.1 Introduction and Objectives25.2 Research Scenario and Test Selection25.3 Research Question and Null Hypothesis25.4 Data Input, Analysis, and Interpretation of Output25.5 Summary25.6 Review Exercises26. Factor Analysis26.1 Introduction and Objectives26.2 Research Scenario and Test Selection26.3 Research Question and Null Hypothesis26.4 Data Input, Analysis, and Interpretation of Output26.5 Summary26.6 Review ExercisesAppendix A. Class Survey Dataset (Entered in Chapter 5)Appendix B. Normal Curve InterpretationAppendix C. Answers to Review Exercises 1, 2, and 3Appendix D. Datasets Listed by ChapterIndex

"I am very appreciative of the authors′ depth and clear writing with comprehensible and useful examples throughout this text."