American Politics: concepts and methodologies 4219-AW232

This course introduces students to the central concepts, questions, and research methods used to study American politics. Rather than focusing exclusively on substantive institutions or contemporary political events, the course examines how political scientists formulate questions about American political life and how they use systematic evidence to answer them. Students will engage with major approaches to the study of American politics, including institutional, behavioral, rational-choice, historical, and comparative perspectives.
The course begins by exploring foundational concepts such as political institutions, representation, political participation, public opinion, parties, interest groups, political behavior, federalism, and political inequality. Particular attention is given to how scholars define and operationalize these concepts and how competing theoretical perspectives generate different expectations about political outcomes.
The second part of the course introduces students to the methodological tools used in political science research. Topics include research design, hypothesis development, measurement and operationalization, case selection, comparative analysis, surveys and experiments, qualitative methods, and the interpretation of quantitative evidence. Students will learn to critically evaluate scholarly arguments, assess the strengths and limitations of different forms of evidence, and distinguish correlation from causation.
Throughout the course, methodological issues are illustrated through substantive debates in American politics. Students will read and analyze influential academic research, develop research questions, assess empirical claims, and practice applying different methodological approaches to political phenomena. By the end of the course, students should be able to identify and evaluate competing explanations of American political outcomes, design basic political science research projects, and communicate empirical arguments clearly and rigorously.
The Scope of Topics for the Course are:
1. Research Topic to Research Question
This section introduces social science research by guiding students from broad topics to precise research questions. It covers transforming ideas into focused inquiries, crafting and refining questions, exploring their origins, and proper phrasing—essential skills for developing the course’s research project and conducting rigorous, meaningful social science investigation.
2. From Research Question to Theory to Hypothesis
This section bridges research questions to theory and hypotheses. It explains how theories provide frameworks for understanding social phenomena, guiding the derivation of testable hypotheses from research questions. Students learn to connect abstract ideas to empirical predictions, forming the foundation for systematic inquiry and the course’s research project.
3. Choosing a Design That Fits Your Question
This section focuses on essential pre-research skills for empirical papers. It outlines the structure of research articles and teaches how to approach academic literatures thoughtfully, clarifying what a literature review is not. Students learn practical methods for finding, organizing, and managing sources and references, then strategies for structuring and writing an effective literature review—building a strong foundation before advancing to theory, hypotheses, and original research design.
4. Choosing a Design That Fits Your Question
This section guides researchers in selecting a design that matches their research question. It distinguishes probabilistic and deterministic hypothesis types, then compares qualitative and quantitative methods—highlighting their similarities, differences, strengths, and weaknesses. Students gain an overview of major analytical techniques in both approaches, enabling informed choices about the most suitable form of analysis for testing hypotheses and advancing the course’s research project with methodological rigor.
5. Case Selection and Study
This section addresses case selection and study design in qualitative research. It explores decisions about the number and choice of cases, the role of background research, and hypothesis-testing strategies. Key techniques covered include content analysis, analytic narratives, case control and controlled comparisons, structured focused comparison, and process tracing—equipping students to design rigorous qualitative studies that effectively test hypotheses and support the course’s research project.
6. Qualitative Data Collection and Management
This section examines qualitative data collection and management. It clarifies the distinctions between information, data, and evidence, addresses measurement challenges, and strategies for maximizing leverage over hypotheses. Students explore types of qualitative sources, the role of counterfactuals, and practical techniques for gathering data from documents and sources used. Guidance on sources, resources, and data management options prepares researchers for systematic evidence collection in support of their research project.
7. Quantitative Data Collection and Management
This section focuses on quantitative data collection and management. It guides researchers in identifying cases through units of analysis, populations, and samples, and selecting variables including controls and multiple indicators. Emphasis is placed on measurement validity, reliability, and operationalization. Students learn to access ready-to-use data from replication datasets and archives, properly cite sources, and collect, code, and manage original data—essential skills for rigorous quantitative research and the course project.
8. Preparing Quantitative Data for Analysis
This introductory section shows students how to get quantitative data ready for analysis. It covers transferring data into a statistics program, handling missing values, naming and labeling variables, and basic checks for common problems. Practical steps include creating new variables, recoding existing ones, and recognizing simple issues that can affect results. The goal is to help beginners prepare clean, usable data so they can confidently test their hypotheses in the research project.