Cover image for IBM SPSS Essentials, 2nd Edition

IBM SPSS Essentials, 2nd Edition

Release Date: 2021/03/01
ISBN: 9781119417422
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Master the fundamentals of SPSS with this newly updated and instructive resource

The newly and thoroughly revised Second Edition of SPSS Essentials delivers a comprehensive guide for students in the social sciences who wish to learn how to use the Statistical Package for the Social Sciences (SPSS) for the effective collection, management, and analysis of data. The accomplished researchers and authors provide readers with the practical nuts and bolts of SPSS usage and data entry, with a particular emphasis on managing and manipulating data. 

The book offers an introduction to SPSS, how to navigate it, and a discussion of how to understand the data the reader is working with. It also covers inferential statistics, including topics like hypothesis testing, one-sample Z-testing, T-testing, ANOVAs, correlations, and regression. Five unique appendices round out the text, providing readers with discussions of dealing with real-world data, troubleshooting, advanced data manipulations, and new workbook activities.

SPSS Essentials offers a wide variety of features, including:

  • A revised chapter order, designed to match the pacing and content of typical undergraduate statistics classes
  • An explanation of when particular inferential statistics are appropriate for use, given the nature of the data being worked with
  • Additional material on understanding your data sample, including discussions of SPSS output and how to find the most relevant information
  • A companion website offering additional problem sets, complete with answers

Perfect for undergraduate students of the social sciences who are just getting started with SPSS, SPSS Essentials also belongs on the bookshelves of advanced placement high school students and practitioners in social science who want to brush up on the fundamentals of this powerful and flexible software package.

Table of Contents

  1. Cover
  2. IBM SPSS Essentials
  3. Copyright
  4. Dedication
  5. Preface
    1. Part I: Introduction
    2. Part II: Statistics
    3. Part III: Advanced Data Management
  6. Acknowledgments
  7. Author Biography
  8. Part I: Introduction
    1. 1 What is SPSS?
    2. Chapter Learning Objectives
    3. What Is SPSS Used For
    4. Summary
    5. 2 Navigating SPSS
    6. Chapter Learning Objectives
    7. How the Program Works
    8. Managing Your SPSS Life
    9. Summary
    10. 3 Introduction to Data
    11. Chapter Learning Objectives
    12. Understanding Your Data
    13. The SPSS Data Perspective
    14. Your Data in SPSS – Think Matrices
    15. Summary
    16. 4 Getting Your Data into SPSS
    17. Chapter Learning Objectives
    18. Before SPSS
    19. Specifying Operations Through SPSS
    20. Numeric Versus String Variables
    21. Data Entry Within the Syntax File
    22. “Saving” Populated Datafiles
    23. Summary
    24. References
    25. Note
    26. 5 Accessing Your Data
    27. Chapter Learning Objectives
    28. Accessing Your Data Files
    29. Importing Data from Excel
    30. Summary
    31. 6 Defining Your Data
    32. Chapter Learning Objectives
    33. Annotation
    34. Defining Your Dataset
    35. Summary
  9. Part II: Statistics
    1. 7 Descriptive Statistics
    2. Chapter Learning Objectives
    3. Frequencies
    4. Displaying Data Graphically
    5. Descriptive Statistics
    6. A General Note on Analyses
    7. A General Note About Output Files
    8. Summary
    9. 8 Hypothesis Testing
    10. Chapter Learning Objectives
    11. Descriptive Versus Inferential Statistics
    12. Hypothesis Testing (A Process for Interpreting Inferential Statistics)
    13. Summary
    14. Notes
    15. 9 Z‐ and T‐Tests
    16. Chapter Learning Objectives
    17. The One Sample Z‐Test
    18. The t‐Test
    19. Summary
    20. Notes
    21. 10 Inferential Analyses (ANOVAs)
    22. Chapter Learning Objectives
    23. One‐Way ANOVA (One‐Way Command)
    24. Repeated‐Measures ANOVA (GLM Command)
    25. Factorial ANOVA (Unianova Command)
    26. Follow‐Up Contrasts
    27. Summary
    28. Reference
    29. 11 Inferential Analyses (Correlation or Regression)
    30. Chapter Learning Objectives
    31. Correlation
    32. Simple Regression
    33. Multiple Regression
    34. Hierarchical Regression
    35. Visualizing Your Relationship
    36. Summary
    37. 12 Nonparametric Analyses
    38. Chapter Learning Objectives
    39. Parametric Versus Nonparametric Analyses
    40. “The” (Pearson's) Chi‐Square: χ2
    41. Summary
    42. Note
  10. Part III: Advanced Data Management
    1. 13 Manipulating Your Data
    2. Chapter Learning Objectives
    3. Creating Scale Scores
    4. How SPSS Thinks About Data
    5. The Importance of Selecting All
    6. Summary
    7. 14 Collapsing and Merging Data Files
    8. Chapter Learning Objectives
    9. Same People, Different Information
    10. Different People, Same Information
    11. Summary
    12. Note
    13. 15 Differential Treatment of Your Data
    14. Chapter Learning Objectives
    15. Isolating Interesting Cases
    16. Summary
    17. 16 Using Your Output
    18. Chapter Learning Objectives
    19. Problem Solving
    20. Maximizing Output Information
    21. Summary
    22. 17 Other Tricks of the Trade
    23. Chapter Learning Objectives
    24. Salvaging Old Syntax
    25. Tricking SPSS To “Think” Across Rows
    26. “Do If” and “End If”
    27. Summary
  11. Appendix A: Appendix ACompleted Questionnaire Form Example
  12. Appendix B: Appendix BExample Code Sheet for Questionnaire
  13. Appendix C: Appendix CSummary of Creating and Defining a Data File
  14. Appendix D: Appendix DExample Syntax File Integrating Multiple Commands (Fulfilling Multiple Purposes)
  15. Appendix E: Appendix ECommands To Know, Organized By Importance
  16. Answers to Chapter Discussion Questions
  17. Index
  18. End User License Agreement
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