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An IBM® SPSS® Companion to Political Analysis
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An IBM® SPSS® Companion to Political Analysis

Sixth Edition
August 2019 | 304 pages | CQ Press
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“[The text] provides by far the best introduction for students wanting to learn how to use SPSS in conducting statistical analysis. Its clear in-depth examples makes data analysis accessible to even the most numbers-phobic student.” 
—Michael Burch, Eckerd College

In Pollock's trusted IBM SPSS® workbook, students dive headfirst into actual political data and work with a software tool that prepares them not only for future political science research, but the job world as well. Students learn by doing with new guided examples, annotated screenshots, step-by-step instructions, and exercises that reflect current scholarly debates in American political behavior and comparative politics. This Sixth Edition of An IBM SPSS® Companion to Political Analysis features thoroughly revised and updated datasets and is compatible with all post-12 releases of SPSS.

Discounted package deals available with the IBM® SPSS® Statistics Base Integrated Student Edition and Philip H. Pollock’s Essentials of Political Analysis. See more information on the “Packages” tab or contact your CQ Press | SAGE sales rep.

Give your students the SAGE edge!
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning. Learn more at edge.sagepub.com/pollock.
 
 
Figures
 
Preface
 
Getting Started
Downloading the Datasets

 
SPSS Full and Grad Pack Versions: What Is the Difference?

 
Watch Screencasts from SAGE Edge

 
 
Chapter 1. Introduction to SPSS
The Data Editor

 
Setting Options for Variable Lists

 
The Viewer

 
Selecting, Printing, and Saving Output

 
How to Format an SPSS Table

 
Saving Commands in Syntax Files

 
Getting Help

 
Chapter 1 Exercises

 
 
Chapter 2. Descriptive Statistics
How SPSS Stores Information about Variables

 
Interpreting Measures of Central Tendency and Variation

 
Describing Nominal Variables

 
Describing Ordinal Variables

 
Using the Chart Editor to Modify Graphics

 
Describing Interval Variables

 
Obtaining Case-level Information with Case Summaries

 
Chapter 2 Exercises

 
 
Chapter 3: Transforming Variables
Creating Indicator Variables

 
Working with Variable Labels

 
Recoding Interval-level Variables into Simplified Categories

 
Simplifying an Internal-level Variable with Visual Binning

 
Centering or Standardizing a Numeric Variable

 
Using Compute to Create an Additive Index

 
Chapter 3 Exercises

 
 
Chapter 4. Making Comparisons
Cross-tabulation Analysis

 
Visualizing Cross-tabulation Analysis with a Bar Chart

 
Mean Comparison Analysis

 
Visualizing Mean Comparison Analysis with a Line Chart

 
Creating a Box Plot to Make Comparisons

 
Chapter 4 Exercises

 
 
Chapter 5. Making Controlled Comparisons
Cross-tabulation Analysis with a Control Variable

 
Graphing Controlled Comparisons with Categorical Dependent Variables

 
Mean Comparison Analysis with a Control Variable

 
Visualizing Controlled Mean Comparisons

 
Chapter 5 Exercises

 
 
Chapter 6. Making Inferences about Sample Means
Finding the 95% Confidence Interval of a Sample Mean

 
Testing a Hypothetical Claim about the Population Mean

 
Inferences about the Difference between Two Sample Means

 
Visualizing Mean Comparisons with Error Bars

 
Making Inferences about Sample Proportions

 
Chapter 6 Exercises

 
 
Chapter 7: Chi-square and Measures of Association
Analyzing an Ordinal-level Relationship

 
Analyzing an Ordinal-level Relationship with a Control Variable

 
Analyzing a Nominal-level Relationship

 
Analyzing a Nominal-level Relationship with a Control Variable

 
Chapter 7 Exercises

 
 
Chapter 8. Correlation and Linear Regression
Correlation Analysis

 
Bivariate Regression

 
Creating Scatterplots for Bivariate Regression Analysis

 
Multiple Regression

 
Visualizing Multiple Regression Analysis with Bubble Plots

 
Chapter 8 Exercises

 
 
Chapter 9. Dummy Variables and Interaction Effects
Regression with Multiple Dummy Variables

 
Interaction Effects in Multiple Regression

 
Graphing Linear Prediction Lines for Interaction Relationships

 
Chapter 9 Exercises

 
 
Chapter 10. Logistic Regression
Thinking about Odds, Logged Odds, and Probabilities

 
Estimating Logistic Regression Models

 
Logistic Regression with Multiple Independent Variables

 
Graphing Predicted Probabilities with One Independent Variable

 
Graphing Predicted Probabilities with Multiple Independent Variables

 
Chapter 10 Exercises

 
 
Chapter 11. Doing Your Own Political Analysis
Seven Doable Ideas

 
Importing Data into SPSS

 
Writing It Up

 
Chapter 11 Exercises

 
 
Appendix, Table A-1: Variables in the GSS Dataset in Alphabetical Order
 
Appendix, Table A-2: Variables in the NES 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

Supplements

Instructor Resources Site
edge.sagepub.com/pollock

Instructor Teaching Site (Password Protected)

SAGE edge for Instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students. This site includes:
  • Datasets that accompany the workbook
  • Syntax files for each chapter of the workbook
  • Solutions Manual that accompanies exercises in the workbook, along with an associated syntax file
  • All tables and figures from the workbook
  • Screencast videos, created by author Philip Pollock, of the guided examples from each chapter
 
Student Study Site
Student Study Site (Open Access)

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment. This site includes:
  • Datasets that accompany the workbook
  • Screencast videos, created by author Philip Pollock, of the guided examples from each chapter, intended to enhance understanding of key topics

“[The text] provides by far the best introduction for students wanting to learn how to use SPSS in conducting statistical analysis. Its clear in-depth examples makes data analysis accessible to even the most numbers-phobic student.”

Michael Burch
Eckerd College

“With a focus on both the mechanics of SPSS and interpretation of data, An IBM SPSS Companion to Political Analysis provides a very useful and useable addition to a Political Science Methods course. The chapters have engaging exercises that address many areas of the discipline and are organized to build students’ understanding of statistical interpretation and skills with SPSS. Students learn to run the statistical procedures, to interpret the results, and to construct arguments with the data.”

Matthew J. Costello
Saint Xavier University

This is a very good resource

Mrs Josephine D Morris
Interdiscipline, Winchester University
December 9, 2020
Report this review
Key features
NEW TO THIS EDITION:
  • Updated Companion datasets can be used for assignments and exercises.
  • Examples drawn from all major subfields reflect current scholarly debates American politics, political behavior, comparative politics, international relations, and law.
  • Reformatted end-of-chapter exercises allow students to tear-out and submit exercises without losing substantive chapter content. 
  • Syntax files for book and chapter exercises are now available to Instructors so they can quickly and easily replicate what's done in the book and the solutions to chapter exercises.
  • A new appendix describes Companion dataset contents—making it easier to use Companion datasets, especially for new exercises and student assignments.
  • QR codes linking to how-to tutorial videos have been added throughout the text to reinforce student learning. 

 

KEY FEATURES:

  • Multiple datasets, guided examples, screenshots, graphics instruction, and end-of-chapter exercises help students with little or no experience with SPPS to learn how to interpret and conduct political analysis
  • The chapters cover all major topics in data analysis—familiarizing students with a wide range of topics, from descriptive statistics to logistic regression.
  • The pages of this book are perforated, three-hole punched, and 8.5” x 11” in size so instructors can use end-of-chapter exercises as homework assignments that students complete and submit.
  • A two-step approach to skill-set learning—(1) Perform the guided examples. (2) Work the exercises—give students opportunities to apply their new skills and to engage students in discovering the meaning of their findings and learning to interpret them
  • Instructors can obtain a complete solution’s manual with instructor’s access to the book’s web site (edge.sagepub.com/pollock). 
  • Screencasts of all of the book's guided examples, plus bonus examples not covered in the book, are available on the student study site.
 

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