Description
SAGE PUBLISHING Political Science Research Methods Ninth Edition 2019 by Johnson
Understand the "how" and the "why" behind research in political science. Political Science Research Methods by Janet Buttolph Johnson, H. T. Reynolds, and Jason D. Mycoff helps you to understand the logic behind research design by guiding you through a step-by-step process that explains when and why a researcher would pursue different kinds of methods. The highly anticipated Ninth Edition of this trusted resource provides more international examples, an increased focus on the role ethics play in the research process, increased attention to qualitative research methods, and expanded coverage on the role of the internet in research and analysis. Tables, Figures, and FeaturesPrefaceAbout the AuthorsChapter 1 * IntroductionResearch on Income InequalityPolitics and the Gender GapThe Case of Italian (Non) Tax ComplianceProtests and Repression in New DemocraciesThe Observer Effect in International Politics: Evidence from a Natural ExperimentConclusionTerms IntroducedChapter 2 * The Empirical Approach to Political ScienceElements of EmpiricismThe Importance of TheoryA Brief Overview of the Empirical Research ProcessReactions to the Empirical Approach: Practical ObjectionsCompeting Points of ViewConclusionTerms IntroducedSuggested ReadingsChapter 3 * Beginning the Research Process: Identifying a Research Topic, Developing Research Questions, and Reviewing the LiteratureSpecifying the Research QuestionSources of Ideas for Research TopicsWhy Conduct a Literature Review?Collecting Sources for a Literature ReviewWriting a Literature ReviewAnatomy of a Literature ReviewConclusionTerms IntroducedSuggested ReadingsChapter 4 * The Building Blocks of Social Scientific Research: Hypotheses, Concepts, Variables, and MeasurementProposing ExplanationsFormulating HypothesesDefining ConceptsDevising Measurement StrategiesThe Accuracy of MeasurementsThe Precision of MeasurementsConclusionTerms IntroducedSuggested ReadingsChapter 5 * SamplingThe Basics of SamplingHow Do We Use a Sample to Learn About a Population?Sampling MethodsTypes of SamplesConclusionTerms IntroducedSuggested ReadingsChapter 6 * Research Design: Establishing CausationVerifying Causal AssertionsQualitative and Quantitative Methods and Analysis: Causes-of-Effects and Effects-of-Causes ApproachesConclusionTerms IntroducedSuggested ReadingsChapter 7 * Qualitative Research: Case Study DesignsCase Study MethodsCase Study TypesUsing Cases to Explore Causal Mechanisms: Process TracingGeneralizing from Cases StudiesConclusionTerms IntroducedSuggested ReadingsChapter 8 * Making Empirical Observations: Qualitative AnalysisTypes of Data and Collection TechniquesData Collection in Qualitative ResearchConclusionTerms IntroducedSuggested ReadingsChapter 9 * Quantitative Research DesignsRandomized Experimental DesignsNatural ExperimentsNonrandomized Designs: Quasi-ExperimentsObservational StudiesConclusionTerms IntroducedSuggested ReadingsChapter 10 * Quantitative MethodsThe Wide Variety of Quantitative ProjectsSources of Data for Quantitative StudiesData ManagementEthical Concerns with Quantitative MethodsConclusionTerms IntroducedSuggested ReadingsChapter 11 * Making Sense of Data: First StepsThe Data MatrixDescriptive StatisticsGraphs for Presentation and ExplorationConclusionTerms IntroducedSuggested ReadingsChapter 12 * Testing RelationshipsThe Normal Distribution and z ScoresConfidence IntervalsHypothesis TestingTesting a Relationship with Two SamplesConclusionTerms IntroducedSuggested ReadingsChapter 13 * Analyzing Relationships for Categorical DataThe Basics of Identifying and Measuring RelationshipsTable Summaries of Categorical Variable AssociationsMeasuring Strength of Relationships in TablesMeasures of Association: Statistics for Reporting the Strength of Relationships in TablesChi Square Test for IndependenceMultivariate Analysis of Categorical DataAnalysis of Variance: Analyzing the Difference between Means for More Than Two MeansConclusionTerms IntroducedSuggested ReadingsChapter 14 * RegressionLogic of RegressionMinimizing the Sum of the Squared ErrorThe Linear Regression ModelMaximum Likelihood Models for Dichotomous Dependent VariablesConclusionTerms IntroducedSuggested ReadingsChapter 15 * The Research Report: An Annotated ExampleAnnotated Research Report ExampleAppendixesAppendix A: Normal Curve Tail ProbabilitiesAppendix B: Critical Values from t DistributionAppendix C: Chi-Squared Distribution Values for Various Right-Tail ProbabilitiesAppendix D: F DistributionGlossaryIndex