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Using IBM SPSS Statistics
An Interactive Hands-On Approach

Third Edition

- James O. Aldrich - California State University, Northridge, USA

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**Other Titles in:**

Quantitative/Statistical Research | Statistical Computing Environments | Study Skills

September 2018 | 504 pages | SAGE Publications, Inc

*Now with a new companion website!*

**Using IBM® SPSS® Statistics: An Interactive Hands-On Approach,**gives readers an accessible and comprehensive guide to walking through SPSS®, providing them with step-by-step knowledge for effectively analyzing their data. From entering data to working with existing databases, and working with the help menu through performing factor analysis,

*Third Edition***Using IBM® SPSS® Statistics**covers every aspect of SPSS® from introductory through intermediate statistics. The book is divided into parts that focus on mastering SPSS® basics, dealing with univariate statistics and graphing, inferential statistics, relational statistics, and more. Written using IBM® SPSS® version 25 and 24, and compatible with the earlier releases, this book is one of the most comprehensive SPSS® guides available.

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

### Supplements

Student Study Website

The open-access** Student Study Site** includes the following:

**Step-by-Step SPSS® Tutorial Videos**created by the author provide screencast demonstrations for 26 key chapter concepts.**Mobile-friendly web quizzes**allow for independent assessment of progress made in learning course material.**A selection of downloadable datasets**for use with end-of-chapter exercises and data entry practice**.**- Direct access to
**SPSS sample files**used in the book.

Instructor Website

Password-protected **Instructor Resources** include the following:

**Pre-written quizzes**provide a diverse range of multiple choice and T/F questions for each chapter, as well as the opportunity to edit questions or insert your own to effectively assess students’ progress and understanding.**Direct access to**used in the book allows instructors to decide which to make available for students, as well as the level and frequency of challenging the student with structuring and entering data.*all*datasets and SPSS sample files**The answers, with explanations, for exercises 4 and 5**found at the end of each chapter, which instructors can assign as homework or exam questions.**Step-by-Step SPSS® Tutorial Videos**created by the author provide screencast demonstrations for 26 key chapter concepts.**Tables and figures**from the book available for download.

“I am very appreciative of the authors' depth and clear writing with comprehensible and useful examples throughout this text.”

Texas A&M University-San Antonio

I teach SPSS for the Psychology class

Psychology, Bowie State University

October 31, 2019

This text is relevant to all of the statistics courses I currently teach. Students often find themselves lost with the steps associated with running statistical analyses in SPSS. It will be adopted and suggested as an additional textbook to assist them with their statistics course as we fully utilize SPSS in our program.

Online & Professional Studies, California Baptist University

October 24, 2019