The Essentials of Political Analysis

Seventh Edition

Philip H. Pollock III - University of Central Florida, USA
Barry C. Edwards - University of Georgia

Available with:

January 2025 | 504 pages | CQ Press

Equip students with the skills and confidence they need to conduct political analyses and critically assess statistical research. In the Seventh Edition of The Essentials of Political Analysis, bestselling authors Philip H. Pollock III and Barry C. Edwards build students' analytic abilities and develop their statistical reasoning with new data, fresh exercises, and clear examples. This brief and reader-friendly guide walks students through the essentials— defining measurement, formulating and testing hypotheses, measuring variables—while using key terms, chapter-opening objectives, nearly 100 tables and figures, and practical exercises to get them using and applying their new skills.

Using Excel, R, SPSS, or STATA? Companion workbooks featuring statistical software instructions and exercises help your students apply their knowledge. See the full suite of companions here.

Available Formats

ISBN: 9781071861462	Paperback	Suggested Retail Price: $142.00	Bookstore Price: $113.60
ISBN: 9781071861530	Electronic Version	Suggested Retail Price: $88.00	Bookstore Price: $70.40
ISBN: 9781071967638	Loose-leaf	Suggested Retail Price: $113.00	Bookstore Price: $90.40

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List of Tables

List of Boxes

Preface

Acknowledgments

About the Authors

Chapter 1 The Definition and Measurement of Concepts

1.1 Conceptual Definitions

1.2 Operational Definitions

1.3 Measurement Error

1.4 Reliability and Validity

1.5 Working With Datasets, Codebooks, and Software

Summary

Key Terms

Exercises

Chapter 2 Measuring and Describing Variables

2.1 Essential Features

2.2 Levels of Measurement

2.3 Central Tendency and Dispersion of Variables

2.4 Describing Nominal-Level Variables

2.5 Describing Ordinal-Level Variables

2.6 Describing Interval-Level Variables

Summary

Key Terms

Exercises

Chapter 3 Creating and Transforming Variables

3.1 Transforming Interval-Level Variables With Math Functions

3.2 Sometimes, Less Is More: Simplifying Variables

3.3 Managing Data and Metadata

3.4 Additive Indexes and Measurement Scales

3.5 Advanced Data Transformation Methods

Summary

Key Terms

Exercises

Chapter 4 Proposing Explanations, Framing Hypotheses, and Making Comparisons

4.1 “All Models Are Wrong, but Some Are Useful”

4.2 Proposing Explanations

4.3 Framing Hypotheses

4.4 Making Comparisons

Summary

Key Terms

Exercises

Chapter 5 Graphing Relationships and Describing Patterns

5.1 Historic Examples of Data Visualization

5.2 Levels of Measurement and Choice of Graph Types

5.3 Visualizing Relationships With Categorical Variables

5.4 Describing Patterns

5.5 Graphing Relationship Between Interval-Level Variables

5.6 Challenges of Visualizing Data

Summary

Key Terms

Exercises

Chapter 6 Research Design, Research Ethics, and Evidence of Causation

6.1 Establishing Causation

6.2 Experimental Designs

6.3 Selecting Cases for Analysis

6.4 Conducting Research Ethically

Summary

Key Terms

Exercises

Chapter 7 Making Controlled Comparisons

7.1 The Logic of Controlled Comparisons

7.2 Essential Terms and Concepts

7.3 Effect of Partisanship on Gun Control Vote, Controlling for Gender: An Illustrative Example

7.4 Controlled Mean Comparisons

7.5 Identifying Patterns

7.6 Advanced Methods of Making Controlled Comparisons

Summary

Key Terms

Exercises

Chapter 8 Foundations of Statistical Inference

8.1 Population Parameters and Sample Statistics

8.2 The Central Limit Theorem and the Normal Distribution

8.3 Quantifying Standard Errors

8.4 Confidence Intervals

8.5 Sample Size and the Margin of Error of a Poll

8.6 Inferences With Small Batches: The Student’s t-Distribution

Summary

Key Terms

Exercises

Chapter 9 Hypothesis Tests With One or Two Samples

9.1 Statistical Significance and Null Hypothesis Testing

9.2 One-Sample Significance Tests

9.3 Two-Sample Significance Tests

9.4 Criticisms of Null Hypothesis Testing

Summary

Key Terms

Exercises

Chapter 10 Chi-Square Test and Analysis of Variance

10.1 Null Hypothesis Tests With More than Two Groups

10.2 The Chi-Square Test of Independence

10.3 Measures of Association

10.4 Analysis of Variance (ANOVA)

Summary

Key Terms

Exercises

Chapter 11 Correlation and Bivariate Regression

11.1 Correlation

11.2 Bivariate Regression

11.3 Educational Attainment and Voter Turnout in States Example

11.4 R-Square and Adjusted R-Square

11.5 All Models Are Still Wrong, but Some Are Useful

Summary

Key Terms

Exercises

Chapter 12 Multiple Regression

12.1 Multiple Regression Equation

12.2 Educational Attainment and Voter Turnout in States Revisited

12.3 Regression With Multiple Dummy Variables

12.4 Interaction Effects in Multiple Regression

12.5 Some Practical Issues in Multiple Regression Analysis

Summary

Key Terms

Exercises

Chapter 13 Analyzing Regression Residuals

13.1 What Are Regression Residuals?

13.2 Assumptions About Regression Residuals

13.3 Diagnostic Graphs of Regression Residuals

13.4 Testing Assumptions About Regression Residuals

13.5 What If Assumptions Are Violated?

Summary

Key Terms

Exercises

Chapter 14 Logistic Regression

14.1 The Logistic Regression Approach

14.2 Logistic Regression Analysis of Vote Choice in the 2020 Presidential Election

14.3 Finding the Best Fit: Maximum Likelihood Estimation

14.4 Logistic Regression With Multiple Independent Variables

14.5 Graphing Predicted Probabilities With Multiple Independent Variables

Summary

Key Terms

Exercises

Chapter 15 Conducting Your Own Political Analysis

15.1 Picking a Good Topic

15.2 Getting Focused and Staying Motivated

15.3 Reviewing Prior Literature

15.4 Collecting Data

15.5 Writing It Up

15.6 Maintain a Scientific Mindset

Summary

Key Terms

Exercises

Glossary

Endnotes

Index

An excellent introduction on how to carry out social scientific research. Highly recommended for undergraduate courses on research design and the basics of statistical analysis.

David Dreyer

Lenoir-Rhyne University

An approachable and lucidly written text that provides students with the essential knowledge and tools for conducting empirical political science research.

Yi Yang

James Madison University

An excellent textbook to use for scope and methods and undergraduate statistics courses.

Maurice Mangum

Jackson State University

A great book that introduces students to the basic elements of research, data, and data analysis. Students don't necessarily need to start the class with a working knowledge of statistics to be successful.

Brian Crisher

University of West Florida

A well-written undergraduate methods textbook that even the most apprehensive student can understand.

Nadine Gibson

University of North Carolina Wilmington

Foundations of statistics for poli sci major in plain language with easy to comprehend exercises.

Volodymyr Guptan

University of Connecticut

Straightforward with good resources.

Youssef Chouhoud

Christopher Newport University

This is a thorough and understandable introduction to research methods that can easily be adapted to your classroom preferences and needs.

Scott Leibertz

University of South Alabama

Key features

NEW TO THIS EDITION:

The new edition is available in Sage Vantage, an intuitive learning platform that integrates quality Sage textbook content with assignable multimedia activities and auto-graded assessments to drive student engagement and ensure accountability. Unparalleled in its ease of use and built for dynamic teaching and learning, Vantage offers customizable LMS integration and best-in-class support.
- Flashcards and note-taking tools help students better prepare for class.
- NEW! Audiobook Player allows students to listen to text content, boosting comprehension and retention. It offers flexible, on-the-go access, engaging both reluctant readers and auditory learners, improving the overall reading experience.
- The Offline Reading option in the Student Dashboard offers greater accessibility to Vantage’s reading content, regardless of where students are or how strong their internet connection may be.
New organization now divides the text into 15 chapters, providing a more structured and manageable approach for instructors and students alike. This now mirrors the companion texts to provide better symmetry.
- Former Chapter 2: Measuring and Describing Variables split into two chapters on "Measuring and Describing Variables" and "Creating and Transforming Variables."
- Former Chapter 3: Proposing Explanations, Framing Hypotheses, and Making Comparisons split into two chapters on "Proposing Explanations, Framing Hypotheses, and Making Comparisons" and "Graphing Relationships and Describing Patterns."
- Finally, former Chapter 8: Correlation and Linear Regression is now split into three chapters on "Correlation and Bivariate Regression," "Multiple Regression," and "Analyzing Regression Residuals."
Expanded material on research ethics discusses new issues such as research transparency, double-blind peer review, P-hacking, and ethical responsibilities when conducting human subject research.
Expanded coverage of data visualization in Chapter 5, Chapter 12, and throughout ensures students learn the skills behind creating clear and useful data visualizations.
New coverage of crucial issues in analysis such as data management, AI in research and analysis, and measures of correlation other than Pearson's ensure the relevance of the book to today's students.
Updated figures and examples throughout the book bring concepts to life by connecting the chapter material to current events, such as the 2020 Presidential Election.

KEY FEATURES:

Clear pedagogy: The Essentials of Political Analysis is organized around a time-honored pedagogical principle: Foreshadow the topic, present the material, and then review the main points.
QR codes linking to author videos reinforce learning by enabling students to hear first-hand from the authors about the material that was discussed in the book.
An emphasis on the supporting role of statistical reasoning helps students describe and interpret the empirical world.
The essentials are presented in a non-statistical context within the first five chapters to enable students think clearly about concepts, describe variables, frame and test hypotheses, evaluate research design, and control for rival explanations.
With these essentials in place, students can appreciate the pivotal role of inferential statistics—introduced and applied, with increasing sophistication, in Chapters 6 through 9.
The final chapter, "Conducting Your Own Political Analysis" guides students through the process of writing an effective research paper.
Most examples use real-world data and are based on analyses of the American National Election Studies (ANES), the General Social Surveys (GSS), a dataset containing variables on many countries, and data on the 50 U.S. states.
Abundant tables and figures—about 100 in all—illustrate methodological concepts and procedures.
End-of-chapter exercises permit students to apply their newly acquired skills.

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