Efnisyfirlit

• Tables, Figures, and Features
• Preface
• About the Authors
• Chapter 1 • Introduction
  • Research on Income Inequality
  • Politics and the Gender Gap
  • The Case of Italian (Non) Tax Compliance
  • Protests and Repression in New Democracies
  • The Observer Effect in International Politics: Evidence from a Natural Experiment
  • Conclusion
  • Terms Introduced
• Chapter 2 • The Empirical Approach to Political Science
  • Elements of Empiricism
  • The Importance of Theory
    • An Example: Proximity Theory of Voting
    • The Explanatory Range of Theories
  • A Brief Overview of the Empirical Research Process
    • Development of an Idea to Investigate or a Problem to Solve
    • Hypothesis Formation
    • “Data” Collection
    • Interpretation and Decision
    • Modification and Extension
  • Reactions to the Empirical Approach: Practical Objections
    • Self-Reflection and Individuality
    • Is Political Science Trivial or Irrelevant?
  • Competing Points of View
    • Interpretation
    • Constructionism and Critical Theory
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 3 • Beginning the Research Process: Identifying a Research Topic, Developing Research Questions, and Reviewing the Literature
  • Specifying the Research Question
  • Sources of Ideas for Research Topics
  • Why Conduct a Literature Review?
  • Collecting Sources for a Literature Review
    • Identifying the Relevant Scholarly Literature
    • Managing Citations
    • Identifying Useful Popular Sources
    • Reading the Literature
  • Writing a Literature Review
  • Anatomy of a Literature Review
    • Scientific Relevance
    • Building a Theory
    • Disagreement in the Literature
    • Data and Methods
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 4 • The Building Blocks of Social Scientific Research: Hypotheses, Concepts, Variables, and Measurement
  • Proposing Explanations
    • Variables
  • Formulating Hypotheses
    • Characteristics of Good Hypotheses
    • Specifying Units of Analysis
    • Cross-Level Analysis: Ecological Inference and Ecological Fallacy
  • Defining Concepts
  • Devising Measurement Strategies
  • The Accuracy of Measurements
    • Reliability
    • Validity
  • The Precision of Measurements
    • Levels of Measurement
    • Working with Precision: Too Little or Too Much
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 5 • Sampling
  • The Basics of Sampling
  • How Do We Use a Sample to Learn about a Population?
    • Sampling Distribution
    • Sample Size and Margin of Error
  • Sampling Methods
  • Types of Samples
    • Simple Random Samples
    • Systematic Random Samples
    • Stratified Samples
    • Cluster Samples
    • Nonprobability Samples
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 6 • Research Design: Establishing Causation
  • Verifying Causal Assertions
    • Causal versus Spurious Relationships
    • The Classical Randomized Experiment
    • Internal Validity
    • External Validity
  • Qualitative and Quantitative Methods and Analysis: Causes-of-Effects and Effects-of-Causes Approaches
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 7 • Qualitative Research: Case Study Designs
  • Case Study Methods
  • Case Study Types
    • Purposes of Case Studies
    • The Logic of Case Selection and Case Comparison
  • Using Cases to Explore Causal Mechanisms: Process Tracing
  • Generalizing from Case Studies
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 8 • Making Empirical Observations: Qualitative Analysis
  • Types of Data and Collection Techniques
    • Choosing among Data Collection Methods
  • Data Collection in Qualitative Research
    • Observation
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 9 • Quantitative Research Designs
  • Randomized Experimental Designs
    • Posttest Design
    • Repeated-Measurement Design
    • Multiple-Group Design
    • Randomized Field Experiments
  • Natural Experiments
  • Nonrandomized Designs: Quasi-Experiments
  • Observational Studies
    • Cross-Sectional Design
    • Longitudinal (Time Series) Designs
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 10 • Quantitative Methods
  • The Wide Variety of Quantitative Projects
  • Sources of Data for Quantitative Studies
    • Content Analysis
    • Content Analysis Procedures
    • Surveys
    • Questionnaire Design Issues
    • Question Wording
    • Question Order
    • Survey Types
  • Data Management
    • Finding and Downloading Data
    • Recording Data
    • Managing Data
  • Ethical Concerns with Quantitative Methods
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 11 • Making Sense of Data: First Steps
  • The Data Matrix
    • Data Description and Exploration
    • Frequency Distributions, Proportions, and Percentages
  • Descriptive Statistics
    • Measures of Central Tendency
    • Resistant Measures
    • Measures of Dispersion
  • Graphs for Presentation and Exploration
    • Designing and Drawing Graphs
    • Bar Charts
    • Exploratory Graphs
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 12 • Testing Relationships
  • The Normal Distribution and z Scores
  • Confidence Intervals
    • Population Confidence Intervals
    • Sample Confidence Intervals
  • Hypothesis Testing
    • Types of Hypotheses
    • Steps for Hypothesis Testing
    • Difference of Means Tests
    • Testing Hypotheses about Proportions
    • Reinforcing Interpretation of Hypothesis Testing
  • Testing a Relationship with Two Samples
    • Difference of Means with Related Samples
    • Difference of Means with Independent Samples
    • Confidence Interval with Two Samples
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 13 • Analyzing Relationships for Categorical Data
  • The Basics of Identifying and Measuring Relationships
    • Level of Measurement
    • Types of Relationships
  • Table Summaries of Categorical Variable Associations
  • Measuring Strength of Relationships in Tables
    • Direction of a Relationship
  • Measures of Association: Statistics for Reporting the Strength of Relationships in Tables
    • A Coefficient for Nominal Data
    • Coefficients for Ordinal Variables
  • Chi-Square Test for Independence
  • Multivariate Analysis of Categorical Data
  • Analysis of Variance: Analyzing the Difference between Means for More Than Two Means
    • Explained and Unexplained Variation
    • Significance Test for Analysis of Variance
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 14 • Regression
  • Logic of Regression
    • The Classical Assumptions of Linear Regression Models
    • Scatterplots
  • Minimizing the Sum of the Squared Error
  • The Linear Regression Model
    • Regression
    • Measuring Correlation: Pearson’s r
    • Measuring the Fit of a Regression Line: R-Squared
    • Multivariate Regression
    • Interpreting Regression Tables
    • Categorical Independent Variables
  • Maximum Likelihood Models for Dichotomous Dependent Variables
    • The Logic of Maximum Likelihood
    • Interpreting a Logistic Regression Table
    • Predicted Probabilities
  • Conclusion
  • Terms Introduced
  • Suggested Readings
• Chapter 15 • The Research Report: An Annotated Example
  • Annotated Research Report Example
• Appendixes
  • Appendix A: Normal Curve Tail Probabilities
  • Appendix B: Critical Values from t Distribution
  • Appendix C: Chi-Squared Distribution Values for Various Right-Tail Probabilities
  • Appendix D: F Distribution
• Glossary
• Index

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