An R Companion for the Third Edition of The Fundamentals of Political Science Research An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten’s best-selling textbook. Built in parallel with the main text, this workbook teachesstudentstoapplythetechniquestheylearnineachchapterbyreproducingthe analyses and results from each lesson using R. Students will also learn to create all of the tables and (cid:30)gures found in the textbook, leading to an even greater mastery of thecorematerial.Thisaccessible,informative,andengagingcompanionwalksthrough theuseofRstep-by-step,usingcommandlinesandscreenshotstodemonstrateproper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluatingcausalclaims.End-of-chapterexercisesencouragethisinnovationbyasking studentstoformulateandevaluatetheirownhypotheses. PaulM.KellstedtisProfessorofPoliticalScienceatTexasA&MUniversity.Heisthe authorofTheMassMediaandtheDynamicsofAmericanRacialAttitudes(Cambridge, 2003),winnerofHarvardUniversity’sJohnF.KennedySchoolofGovernment’s2004 Goldsmith Book Prize. In addition, he has published numerous articles in a variety of leading journals. He is the Editor-in-chief of Political Science Research and Methods, the(cid:31)agshipjournaloftheEuropeanPoliticalScienceAssociation. GuyD.WhittenisCullen-McFaddenProfessorofPoliticalScience,aswellasDirector of the European Union Center, at Texas A&M University. He has published a variety of articles in leading peer-reviewed journals. He is on the editorial boards of Political AnalysisandPoliticalScienceResearchandMethods. An R Companion for the Third Edition of The Fundamentals of Political Science Research Paul M. Kellstedt TexasA&MUniversity Guy D. Whitten TexasA&MUniversity UniversityPrintingHouse,CambridgeCB28BS,UnitedKingdom OneLibertyPlaza,20thFloor,NewYork,NY10006,USA 477WilliamstownRoad,PortMelbourne,VIC3207,Australia 314–321,3rdFloor,Plot3,SplendorForum,JasolaDistrictCentre, NewDelhi–110025,India 79AnsonRoad,#06–04/06,Singapore079906 CambridgeUniversityPressispartoftheUniversityofCambridge. ItfurtherstheUniversity’smissionbydisseminatingknowledgeinthepursuitof education,learning,andresearchatthehighestinternationallevelsofexcellence. www.cambridge.org Informationonthistitle:www.cambridge.org/9781108446037 DOI:10.1017/9781108601832 ©PaulM.KellstedtandGuyD.Whitten2021 Thispublicationisincopyright.Subjecttostatutoryexception andtotheprovisionsofrelevantcollectivelicensingagreements, noreproductionofanypartmaytakeplacewithoutthewritten permissionofCambridgeUniversityPress. Firstpublished2021 AcataloguerecordforthispublicationisavailablefromtheBritishLibrary. ISBN978-1-108-44603-7Paperback Additionalresourcesforthispublicationatwww.cambridge.org/FPSR-R CambridgeUniversityPresshasnoresponsibilityforthepersistenceoraccuracyof URLsforexternalorthird-partyinternetwebsitesreferredtointhispublication anddoesnotguaranteethatanycontentonsuchwebsitesis,orwillremain, accurateorappropriate. BRIEF CONTENTS Preface pagexi ListofFigures xiii 1 TheScientiicStudyofPolitics 1 2 TheArtofTheoryBuilding 9 3 EvaluatingCausalRelationships 19 4 ResearchDesign 22 5 MeasuringConceptsofInterest 24 6 GettingtoKnowYourData 27 7 ProbabilityandStatisticalInference 35 8 BivariateHypothesisTesting 42 9 Two-VariableRegressionModels 50 10 MultipleRegression:TheBasics 53 11 MultipleRegressionModelSpeciication 58 12 LimitedDependentVariablesandTime-SeriesData 66 Bibliography 71 Index 73 v CONTENTS Preface pagexi ListofFigures xiii 1 TheScientiicStudyofPolitics 1 1.1 Overview 1 1.2 “AWorkbook?WhyIsThereaWorkbook?” 1 1.2.1 ReadingCommandsinThisWorkbook 2 1.3 GettingStartedwithRandRStudio 2 1.3.1 LaunchingRStudio 3 1.3.2 GettingRtoDoThings 3 1.3.3 InitiallyExaminingDatainR 6 1.3.4 AddingNotestoScriptFilesandSavingThem 7 1.4 Exercises 8 2 TheArtofTheoryBuilding 9 2.1 Overview 9 2.2 RPackages 9 2.3 ExaminingVariationacrossTimeandacrossSpace 10 2.3.1 ProducingaBarGraphforExaminingCross-SectionVariation 11 2.3.2 Producing a Connected Plot for Examining Time-Series Variation 13 2.4 UsingGoogleScholartoSearchtheLiteratureEffectively 14 2.5 WrappingUp 18 2.6 Exercises 18 3 EvaluatingCausalRelationships 19 3.1 Overview 19 3.2 Exercises 19 4 ResearchDesign 22 4.1 Overview 22 4.2 Exercises 22 vii viii CONTENTS 5 MeasuringConceptsofInterest 24 5.1 Overview 24 5.2 Exercises 24 6 GettingtoKnowYourData 27 6.1 Overview 27 6.2 DescribingCategoricalandOrdinalVariables 27 6.3 DescribingContinuousVariables 30 6.4 PuttingStatisticalOutputintoTables,Documents,andPresentations 32 6.5 Exercises 33 7 ProbabilityandStatisticalInference 35 7.1 Overview 35 7.2 DiceRollinginR 35 7.3 Exercises 40 8 BivariateHypothesisTesting 42 8.1 Overview 42 8.2 TabularAnalysis 42 8.2.1 GeneratingTestStatistics 43 8.2.2 PuttingTabularResultsintoPapers 44 8.3 DifferenceofMeans 45 8.3.1 ExaminingDifferencesGraphically 45 8.3.2 GeneratingTestStatistics 45 8.4 CorrelationCoef(cid:30)cients 46 8.4.1 ProducingScatterPlots 46 8.4.2 GeneratingCovarianceTablesandTestStatistics 47 8.5 Exercises 48 9 Two-VariableRegressionModels 50 9.1 Overview 50 9.2 EstimatingaTwo-VariableRegression 50 9.3 GraphingaTwo-VariableRegression 51 9.4 Exercises 52 10 MultipleRegression:TheBasics 53 10.1 Overview 53 10.2 EstimatingaMultipleRegression 53 10.3 From Regression Output to Table – Making Only One Type ofComparison 54 10.3.1 Comparing Models with the Same Sample of Data, but DifferentSpeci(cid:30)cations 54 10.3.2 ComparingModelswiththeSameSpeci(cid:30)cation,butDifferent SamplesofData 55 CONTENTS ix 10.4 StandardizedCoef(cid:30)cients 56 10.5 Exercises 56 11 MultipleRegressionModelSpeciication 58 11.1 Overview 58 11.2 DummyVariables 58 11.2.1 CreatingNewVariables 58 11.2.2 Estimating a Multiple Regression Model with a Single DummyIndependentVariable 60 11.2.3 Estimating a Multiple Regression Model with Multiple DummyIndependentVariables 60 11.3 DummyVariablesinInteractions 61 11.4 Post-estimationDiagnosticsinRforOLS 61 11.4.1 IdentifyingOutliersandIn(cid:31)uentialCasesinOLS 61 11.5 Exercises 64 12 LimitedDependentVariablesandTime-SeriesData 66 12.1 Overview 66 12.2 ModelswithDummyDependentVariables 66 12.3 Exercises 70 Bibliography 71 Index 73