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Using IBM® SPSS® Statistics
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Using IBM® SPSS® Statistics
An Interactive Hands-On Approach

Third Edition


September 2018 | 504 pages | SAGE Publications, Inc

Now with a new companion website!  

Using IBM® SPSS® Statistics: An Interactive Hands-On Approach, Third Edition 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, 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.  

Bundle Using IBM® SPSS® Statistics: An Interactive Hands-On Approach with SAGE IBM® SPSS® Statistics v24.0 Student Version and SAVE! – Bundle ISBN: 978-1-5443-5071-4

 
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 all datasets and SPSS sample files 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.
  • 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.”

Dr. Billy R. Brocato
Texas A&M University-San Antonio
Key features

NEW TO THIS EDITION:  

  • A new Companion Website enhances the mastery of concepts and includes:
    • Downloadable datasets for practice
    • Video tutorials from the author that guide readers through SPSS functionality
    • 100 pages of answers that provide detailed explanations as well as graphs and tables directly from the SPSS output.
    • Answers to the two additional Review Exercises at the end of each chapter that are available to instructors.
  • Each statistical chapter has additional descriptions of the goals and parameters of each statistical test and the basic formula behind the test.
  • The entire text has been updated to reflect the changes of SPSS version 25.
  • A new chapter on inferential statistics helps readers transition from univariate to inferential tests.
    • Topics such as sampling, statistical significance and hypothesis testing are addressed to give the SPSS user a foundational understanding of the results of SPSS’s statistical procedures
  • A new Appendix provides examples of the use of the normal curve and z-table to solve probability type problems that encourages the student/statistician to examine and understand the real meaning and importance of the “Sig. (2-tailed)” column shown in much of SPSS’s output.

KEY FEATURES:

  • This book makes the benefits of the latest SPSS program available not only to the novice but also to the more experienced user of statistics.
  • Chapter objectives alert readers to what they’ll learn in the pages that follow.
  • Bulleted, step-by-step instructions for doing statistical analysis include items the reader should click on in bold and other important terms in italics.
  • Screenshots and callouts present additional details on where to click, unclick, and enter variable information and/or data.
  • Nonparametric tests are included in the same chapters as their related parametric tests to help readers find the information they need more quickly.
  • Review Exercises (5 for each chapter) provide additional hands-on practice. Detailed answers and explanations for the first 3 can be found in the appendix and the final 2 are available to instructors only at study.sagepub.com/aldrich3e.

 


Sample Materials & Chapters

Chapter 1 - First Encounters

Chapter 24 - Multiple Linear Regression


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