An IBM (R) SPSS (R) Companion to Political Analysis
7th Edition
Published on 18. August 2025
Book
Paperback/Softback
424 pages
978-1-0718-6147-9 (ISBN)
Description
An IBM (R) SPSS (R) Companion to Political Analysis equips students with practical political data skills using updated datasets from GSS and ANES, including 2020 election variables. The Seventh Edition enhances learning with new data and examples, newly-divided chapters, and hands-on exercises, preparing students for research and careers in political science.
More details
Edition
7th Revised edition
Language
English
Place of publication
Washington
United States
Publishing group
SAGE Publications Inc
Target group
College/higher education
Edition type
Revised edition
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 274 mm
Width: 211 mm
Thickness: 18 mm
Weight
1111 gr
ISBN-13
978-1-0718-6147-9 (9781071861479)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Philip H. Pollock | Barry Clayton Edwards
An IBM (R) SPSS (R) Companion to Political Analysis
Book
10/2019
6th Edition
CQ Press
€94.28
Article exhausted; check for reprint
Persons
Philip H. Pollock III is a professor of political science at the University of Central Florida. He has taught courses in research methods at the undergraduate and graduate levels for more than thirty years. His main research interests are American public opinion, voting behavior, techniques of quantitative analysis, and the scholarship of teaching and learning. His recent research has been on the effectiveness of Internet-based instruction. Pollock's research has appeared in the American Journal of Political Science, Social Science Quarterly, and the British Journal of Political Science. Recent scholarly publications include articles in Political Research Quarterly, the Journal of Political Science Education, and PS: Political Science and Politics.
Barry C. Edwards writes textbooks and works for Fair Trial Analysis, LLC, a company that conducts research on juries and jurors for civil and criminal litigation. He received his B.A. from Stanford University, a J.D. from New York University, and a Ph.D. from the University of Georgia. He taught survey design and analysis, research methods, and prelaw courses at the University of Central Florida and continues to teach occasional courses for the University of Georgia. His political science interests include American politics, public law, and research methods. He founded the Political Science Data Group and created the PoliSciData.com website. His research has been published in American Politics Research, Congress & the Presidency, Election Law Journal, Emory Law Journal, Georgia Bar Journal, Harvard Negotiation Law Review, Journal of Politics, NYU Journal of Legislation and Public Policy, Political Research Quarterly, Presidential Studies Quarterly, Public Management Review, State Politics and Policy Quarterly, and UCLA Criminal Justice Law Review.
Barry C. Edwards writes textbooks and works for Fair Trial Analysis, LLC, a company that conducts research on juries and jurors for civil and criminal litigation. He received his B.A. from Stanford University, a J.D. from New York University, and a Ph.D. from the University of Georgia. He taught survey design and analysis, research methods, and prelaw courses at the University of Central Florida and continues to teach occasional courses for the University of Georgia. His political science interests include American politics, public law, and research methods. He founded the Political Science Data Group and created the PoliSciData.com website. His research has been published in American Politics Research, Congress & the Presidency, Election Law Journal, Emory Law Journal, Georgia Bar Journal, Harvard Negotiation Law Review, Journal of Politics, NYU Journal of Legislation and Public Policy, Political Research Quarterly, Presidential Studies Quarterly, Public Management Review, State Politics and Policy Quarterly, and UCLA Criminal Justice Law Review.
Content
Figures
Preface
Acknowledgements
About the Authors
Introduction: Getting Started with SPSS
I.1 Downloading the Datasets
I.2 SPSS Full and Student Versions: What's the Difference?
I.3 Watch Screencasts from SAGE Edge
Chapter 1: Using SPSS for Data Analysis
1.1 The Data Editor
1.2 Setting Options for Variable Lists
1.3 The Viewer
1.4 Selecting, Printing, and Saving Output
1.5 How to Format an SPSS Table
1.6 Saving Commands in Syntax Files
1.7 Getting Help
1.8 Chapter Review
Chapter 1 Exercises
Chapter 2: Descriptive Statistics
2.1 How SPSS Stores Information about Variables
2.2 Identifying Levels of Measurement
2.3 Describing Nominal Variables
2.4 Describing Ordinal Variables
2.5 Describing Interval Variables
2.6 Using the Chart Editor to Modify Graphics
2.7 Obtaining Case-level Information with Case Summaries
2.8 Chapter Review
Chapter 2 Exercises
Chapter 3: Creating and Transforming Variables
3.1 Creating Indicator Variables
3.2 Working with Variable Labels
3.3 Recoding Interval-level Variables into Simplified Categories
3.4 Simplifying an Internal-level Variable with Visual Binning
3.5 Centering or Standardizing a Numeric Variable
3.6 Using Compute to Create an Additive Index
3.7 Chapter Review
Chapter 3 Exercises
Chapter 4: Making Comparisons
4.1 Cross-Tabulation Analysis
4.2 Visualizing Cross-Tabulation Analysis with a Bar Chart
4.3 Mean Comparison Analysis
4.4 Visualizing Mean Comparison Analysis with a Line Chart
4.5 Making Comparisons with Interval-Level Independent Variables
4.6 Chapter Review
Chapter 4 Exercises
Chapter 5: Graphing Relationships and Describing Patterns
5.1 Graphs for Binary Dependent Variables
5.2 Graphs for Nominal Dependent Variables
5.3 Graphs for Ordinal-Level Dependent Variables
5.4 Graphs for Interval-Level Dependent Variables
5.5 Chapter Review
Chapter 5 Exercises
Chapter 6: Random Assignment and Sampling
6.1 Random Assignment
6.2 Analyzing the Results of an Experiment
6.3 Random Sampling
6.4 Selecting Cases for Qualitative Analysis
6.5 Analyzing Data Ethically
6.6 Chapter Review
Chapter 6 Exercises
Chapter 7: Making Controlled Comparisons
7.1 Cross-Tabulation Analysis with a Control Variable
7.2 Graphs for Controlled Cross-Tabulations
7.3 Mean Comparison Analysis with a Control Variable
7.4 Visualizing Controlled Mean Comparisons
7.5 Controlled Comparisons with Interval-Level Control Variables
7.6 Chapter Review
Chapter 7 Exercises
Chapter 8: Foundations of Statistical Inference
8.1 Estimating a Population Proportion with Computer Simulation
8.2 Expected Shape of Sampling Distributions
8.3 Confidence Intervals and Margins of Error
8.4 Student's t-Distribution: When You're Not Completely Normal
8.5 Chapter Review
Chapter 8 Exercises
Chapter 9: Hypothesis Tests with One or Two Samples
9.1 Role of the Null Hypothesis
9.2 Testing Hypothesis about a Population Proportion
9.3 Testing Hypothesis about Difference between Two Population Proportions
9.4 Testing Hypothesis about Population Mean
9.5 Testing Hypothesis about Difference between Two Population Means
9.6 Chapter Review
Chapter 9 Exercises
Chapter 10: Chi-Square Test and Analysis of Variance
10.1 The Chi-Square Test of Independence
10.2 Measuring the Strength of Association between Categorical Variables
10.3 Chi-Square Test and Measures of Association in Controlled Comparisons
10.4 Analysis of Variance
10.5 Chapter Review
Chapter 10 Exercises
Chapter 11: Correlation and Bivariate Regression
11.1 Correlation Analysis
11.2 Bivariate Regression
11.3 Creating Scatterplots for Bivariate Regression Analysis
11.4 Chapter Review
Chapter 11 Exercises
Chapter 12: Multiple Regression
12.1 Estimating and Interpreting Multiple Regression
12.2 Regression with Multiple Dummy Variables
12.3 Interaction Effects in Multiple Regression
12.4 Visualizing Multiple Regression Analysis with Bubble Plots
12.5 Graphing Interaction Relationships
12.6 Chapter Review
Chapter 12 Exercises
Chapter 13: Analyzing Regression Residuals
13.1 Expected Values, Observed Values, and Regression Residuals
13.2 Squared and Standardized Residuals
13.3 Assumptions about Regression Residuals
13.4 Analyzing Graphs of Regression Residuals
13.5 Testing Regression Assumptions with Residual Values
13.6 Identifying Outliers and Influential Observations
13.7 What If You Diagnose Problems with Residuals?
13.8 Chapter Review
Chapter 13 Exercises
Chapter 14: Logistic Regression
14.1 Odds, Logged Odds, and Probabilities
14.2 Estimating Logistic Regression Models
14.3 Graphing Predicted Probabilities with One Independent Variable
14.4 Logistic Regression with Multiple Independent Variables
14.5 Graphing Predicted Probabilities with Multiple Independent Variables
14.6 Chapter Review
Chapter 14 Exercises
Chapter 15 Doing Your Own Political Analysis
15.1 Doable Research Ideas
15.2 Importing Data into SPSS
15.3 Writing It Up
15.4 Chapter Review
Chapter 15 Exercises
Appendix, Table A-1: Variables in the GSS Dataset in Alphabetical Order
Appendix, Table A-2: Variables in the ANES Dataset in Alphabetical Order
Appendix, Table A-3: Variables in the States Dataset by Topic
Appendix, Table A-4: Variables in the World Dataset by Topic
Preface
Acknowledgements
About the Authors
Introduction: Getting Started with SPSS
I.1 Downloading the Datasets
I.2 SPSS Full and Student Versions: What's the Difference?
I.3 Watch Screencasts from SAGE Edge
Chapter 1: Using SPSS for Data Analysis
1.1 The Data Editor
1.2 Setting Options for Variable Lists
1.3 The Viewer
1.4 Selecting, Printing, and Saving Output
1.5 How to Format an SPSS Table
1.6 Saving Commands in Syntax Files
1.7 Getting Help
1.8 Chapter Review
Chapter 1 Exercises
Chapter 2: Descriptive Statistics
2.1 How SPSS Stores Information about Variables
2.2 Identifying Levels of Measurement
2.3 Describing Nominal Variables
2.4 Describing Ordinal Variables
2.5 Describing Interval Variables
2.6 Using the Chart Editor to Modify Graphics
2.7 Obtaining Case-level Information with Case Summaries
2.8 Chapter Review
Chapter 2 Exercises
Chapter 3: Creating and Transforming Variables
3.1 Creating Indicator Variables
3.2 Working with Variable Labels
3.3 Recoding Interval-level Variables into Simplified Categories
3.4 Simplifying an Internal-level Variable with Visual Binning
3.5 Centering or Standardizing a Numeric Variable
3.6 Using Compute to Create an Additive Index
3.7 Chapter Review
Chapter 3 Exercises
Chapter 4: Making Comparisons
4.1 Cross-Tabulation Analysis
4.2 Visualizing Cross-Tabulation Analysis with a Bar Chart
4.3 Mean Comparison Analysis
4.4 Visualizing Mean Comparison Analysis with a Line Chart
4.5 Making Comparisons with Interval-Level Independent Variables
4.6 Chapter Review
Chapter 4 Exercises
Chapter 5: Graphing Relationships and Describing Patterns
5.1 Graphs for Binary Dependent Variables
5.2 Graphs for Nominal Dependent Variables
5.3 Graphs for Ordinal-Level Dependent Variables
5.4 Graphs for Interval-Level Dependent Variables
5.5 Chapter Review
Chapter 5 Exercises
Chapter 6: Random Assignment and Sampling
6.1 Random Assignment
6.2 Analyzing the Results of an Experiment
6.3 Random Sampling
6.4 Selecting Cases for Qualitative Analysis
6.5 Analyzing Data Ethically
6.6 Chapter Review
Chapter 6 Exercises
Chapter 7: Making Controlled Comparisons
7.1 Cross-Tabulation Analysis with a Control Variable
7.2 Graphs for Controlled Cross-Tabulations
7.3 Mean Comparison Analysis with a Control Variable
7.4 Visualizing Controlled Mean Comparisons
7.5 Controlled Comparisons with Interval-Level Control Variables
7.6 Chapter Review
Chapter 7 Exercises
Chapter 8: Foundations of Statistical Inference
8.1 Estimating a Population Proportion with Computer Simulation
8.2 Expected Shape of Sampling Distributions
8.3 Confidence Intervals and Margins of Error
8.4 Student's t-Distribution: When You're Not Completely Normal
8.5 Chapter Review
Chapter 8 Exercises
Chapter 9: Hypothesis Tests with One or Two Samples
9.1 Role of the Null Hypothesis
9.2 Testing Hypothesis about a Population Proportion
9.3 Testing Hypothesis about Difference between Two Population Proportions
9.4 Testing Hypothesis about Population Mean
9.5 Testing Hypothesis about Difference between Two Population Means
9.6 Chapter Review
Chapter 9 Exercises
Chapter 10: Chi-Square Test and Analysis of Variance
10.1 The Chi-Square Test of Independence
10.2 Measuring the Strength of Association between Categorical Variables
10.3 Chi-Square Test and Measures of Association in Controlled Comparisons
10.4 Analysis of Variance
10.5 Chapter Review
Chapter 10 Exercises
Chapter 11: Correlation and Bivariate Regression
11.1 Correlation Analysis
11.2 Bivariate Regression
11.3 Creating Scatterplots for Bivariate Regression Analysis
11.4 Chapter Review
Chapter 11 Exercises
Chapter 12: Multiple Regression
12.1 Estimating and Interpreting Multiple Regression
12.2 Regression with Multiple Dummy Variables
12.3 Interaction Effects in Multiple Regression
12.4 Visualizing Multiple Regression Analysis with Bubble Plots
12.5 Graphing Interaction Relationships
12.6 Chapter Review
Chapter 12 Exercises
Chapter 13: Analyzing Regression Residuals
13.1 Expected Values, Observed Values, and Regression Residuals
13.2 Squared and Standardized Residuals
13.3 Assumptions about Regression Residuals
13.4 Analyzing Graphs of Regression Residuals
13.5 Testing Regression Assumptions with Residual Values
13.6 Identifying Outliers and Influential Observations
13.7 What If You Diagnose Problems with Residuals?
13.8 Chapter Review
Chapter 13 Exercises
Chapter 14: Logistic Regression
14.1 Odds, Logged Odds, and Probabilities
14.2 Estimating Logistic Regression Models
14.3 Graphing Predicted Probabilities with One Independent Variable
14.4 Logistic Regression with Multiple Independent Variables
14.5 Graphing Predicted Probabilities with Multiple Independent Variables
14.6 Chapter Review
Chapter 14 Exercises
Chapter 15 Doing Your Own Political Analysis
15.1 Doable Research Ideas
15.2 Importing Data into SPSS
15.3 Writing It Up
15.4 Chapter Review
Chapter 15 Exercises
Appendix, Table A-1: Variables in the GSS Dataset in Alphabetical Order
Appendix, Table A-2: Variables in the ANES Dataset in Alphabetical Order
Appendix, Table A-3: Variables in the States Dataset by Topic
Appendix, Table A-4: Variables in the World Dataset by Topic