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.

"A great resource to get students up and running on statistical analysis in politics. I recommend this book to all my colleagues. The accompanying workbook for R is also excellent."

• Tables, Figures, and BoxesPrefaceAcknowledgmentsAbout the AuthorsIntroductionFacts and Values in PerspectiveThe Scientific ApproachWhat This Book Is AboutConclusionKey TermsNotesCHAPTER 1 • The Definition and Measurement of ConceptsLearning ObjectivesConceptual DefinitionsOperational DefinitionsMeasurement ErrorReliability and ValidityWorking with Datasets, Codebooks, and SoftwareSummaryKey TermsExercisesNotesCHAPTER 2 • Measuring and Describing VariablesLearning ObjectivesEssential FeaturesLevels of MeasurementDescribing VariablesTransforming VariablesSummaryKey TermsExercisesNotesCHAPTER 3 • Proposing Explanations, Framing Hypotheses, and Making ComparisonsLearning Objectives“All Models Are Wrong, But Some Are Useful”Proposing ExplanationsFraming HypothesesCommon Mistakes in Hypothesis WritingMaking ComparisonsGraphing Relationships and Describing PatternsSummaryKey TermsExercisesNotesCHAPTER 4 • Research Design, Research Ethics, and Evidence of CausationLearning ObjectivesEstablishing CausationExperimental DesignsSelecting Cases for AnalysisConducting Research EthicallySummaryKey TermsExercisesNotesCHAPTER 5 • Making Controlled ComparisonsLearning ObjectivesThe Logic of Controlled ComparisonsEssential Terms and ConceptsEffect of Partisanship on Gun Control Vote, Controlling for Gender: An Illustrative ExampleControlled Mean ComparisonsIdentifying PatternsAdvanced Methods of Making Controlled ComparisonsSummaryKey TermsExercisesNotesCHAPTER 6 • Foundations of Statistical InferenceLearning ObjectivesPopulation Parameters and Sample StatisticsThe Central Limit Theorem and the Normal DistributionQuantifying Standard ErrorsConfidence IntervalsSample Size and the Margin of Error of a PollInferences with Small Batches: The Student’s t-DistributionSummaryKey TermsExercisesNotesCHAPTER 7 • Tests of Significance and Measures of AssociationLearning ObjectivesStatistical Significance and Null Hypothesis TestingOne-Sample Significance TestsTwo-Sample Significance TestsThe Chi-square TestMeasures of AssociationCriticisms of Null Hypothesis TestingSummaryKey TermsExercisesNotesCHAPTER 8 • Correlation and Linear RegressionLearning ObjectivesCorrelationBivariate RegressionEducational Attainment and Voter Turnout in States ExampleR-squareMultiple RegressionSome Practical Issues: Multicollinearity, Parsimony, and Missing DataAnalyzing Residuals to Evaluate Linear Regression ModelsSummaryKey TermsExercisesNotesCHAPTER 9 • Logistic RegressionLearning ObjectivesThe Logistic Regression ApproachLogistic Regression Approach to Vote Choice in the 2016 Presidential ElectionFinding the Best Fit: Maximum Likelihood EstimationLogistic Regression with Multiple Independent VariablesGraphing Predicted Probabilities with Multiple Independent VariablesSummaryKey TermsExercisesNotesCHAPTER 10 • Conducting Your Own Political AnalysisPicking a Good TopicGetting Focused and Staying MotivatedReviewing Prior LiteratureCollecting DataWriting It UpMaintain a Scientific MindsetKey TermsExercisesNotesIndex