The Essentials of Political Analysis

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.

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

• List of TablesList of BoxesPrefaceAcknowledgmentsAbout the AuthorsChapter 1 The Definition and Measurement of Concepts1.1 Conceptual Definitions1.2 Operational Definitions1.3 Measurement Error1.4 Reliability and Validity1.5 Working With Datasets, Codebooks, and SoftwareSummaryKey TermsExercisesChapter 2 Measuring and Describing Variables2.1 Essential Features2.2 Levels of Measurement2.3 Central Tendency and Dispersion of Variables2.4 Describing Nominal-Level Variables2.5 Describing Ordinal-Level Variables2.6 Describing Interval-Level VariablesSummaryKey TermsExercisesChapter 3 Creating and Transforming Variables3.1 Transforming Interval-Level Variables With Math Functions3.2 Sometimes, Less Is More: Simplifying Variables3.3 Managing Data and Metadata3.4 Additive Indexes and Measurement Scales3.5 Advanced Data Transformation MethodsSummaryKey TermsExercisesChapter 4 Proposing Explanations, Framing Hypotheses, and Making Comparisons4.1 “All Models Are Wrong, but Some Are Useful”4.2 Proposing Explanations4.3 Framing Hypotheses4.4 Making ComparisonsSummaryKey TermsExercisesChapter 5 Graphing Relationships and Describing Patterns5.1 Historic Examples of Data Visualization5.2 Levels of Measurement and Choice of Graph Types5.3 Visualizing Relationships With Categorical Variables5.4 Describing Patterns5.5 Graphing Relationship Between Interval-Level Variables5.6 Challenges of Visualizing DataSummaryKey TermsExercisesChapter 6 Research Design, Research Ethics, and Evidence of Causation6.1 Establishing Causation6.2 Experimental Designs6.3 Selecting Cases for Analysis6.4 Conducting Research EthicallySummaryKey TermsExercisesChapter 7 Making Controlled Comparisons7.1 The Logic of Controlled Comparisons7.2 Essential Terms and Concepts7.3 Effect of Partisanship on Gun Control Vote, Controlling for Gender: An Illustrative Example7.4 Controlled Mean Comparisons7.5 Identifying Patterns7.6 Advanced Methods of Making Controlled ComparisonsSummaryKey TermsExercisesChapter 8 Foundations of Statistical Inference8.1 Population Parameters and Sample Statistics8.2 The Central Limit Theorem and the Normal Distribution8.3 Quantifying Standard Errors8.4 Confidence Intervals8.5 Sample Size and the Margin of Error of a Poll8.6 Inferences With Small Batches: The Student’s t-DistributionSummaryKey TermsExercisesChapter 9 Hypothesis Tests With One or Two Samples9.1 Statistical Significance and Null Hypothesis Testing9.2 One-Sample Significance Tests9.3 Two-Sample Significance Tests9.4 Criticisms of Null Hypothesis TestingSummaryKey TermsExercisesChapter 10 Chi-Square Test and Analysis of Variance10.1 Null Hypothesis Tests With More than Two Groups10.2 The Chi-Square Test of Independence10.3 Measures of Association10.4 Analysis of Variance (ANOVA)SummaryKey TermsExercisesChapter 11 Correlation and Bivariate Regression11.1 Correlation11.2 Bivariate Regression11.3 Educational Attainment and Voter Turnout in States Example11.4 R-Square and Adjusted R-Square11.5 All Models Are Still Wrong, but Some Are UsefulSummaryKey TermsExercisesChapter 12 Multiple Regression12.1 Multiple Regression Equation12.2 Educational Attainment and Voter Turnout in States Revisited12.3 Regression With Multiple Dummy Variables12.4 Interaction Effects in Multiple Regression12.5 Some Practical Issues in Multiple Regression AnalysisSummaryKey TermsExercisesChapter 13 Analyzing Regression Residuals13.1 What Are Regression Residuals?13.2 Assumptions About Regression Residuals13.3 Diagnostic Graphs of Regression Residuals13.4 Testing Assumptions About Regression Residuals13.5 What If Assumptions Are Violated?SummaryKey TermsExercisesChapter 14 Logistic Regression14.1 The Logistic Regression Approach14.2 Logistic Regression Analysis of Vote Choice in the 2020 Presidential Election14.3 Finding the Best Fit: Maximum Likelihood Estimation14.4 Logistic Regression With Multiple Independent Variables14.5 Graphing Predicted Probabilities With Multiple Independent VariablesSummaryKey TermsExercisesChapter 15 Conducting Your Own Political Analysis15.1 Picking a Good Topic15.2 Getting Focused and Staying Motivated15.3 Reviewing Prior Literature15.4 Collecting Data15.5 Writing It Up15.6 Maintain a Scientific MindsetSummaryKey TermsExercisesGlossaryEndnotesIndex