Teaching History

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This course provides an introduction to the methodology of political science research for undergraduate students. The first part of this course serves the logic of social scientific inquiry and the basics of research design. Next, the course introduces students to the quantitative and qualitative methods that are commonly used by political scientists to investigate important questions about the political world. The main goals of this course are (1) to familiarize quantitative and quantitative research, with the ability to see the strengths and flaws of social scientific studies in academic journals and books, newspapers, web sites and other outlets; and (2) to give students the skills necessary to begin conducting original political science research studies of their own. Through this course, students will develop a critical understanding of issues related to scientific inquiry, measurement, causal inference, experimental, quasi-experimental and observational research, formal modeling, and sampling and survey research. Also, students will learn fundamental concepts in descriptive and inferential statistical reasoning, and data analytic techniques such as t-test, crosstabulation, and regression analysis, and will develop the skills to apply these methods using the R statistical package.

This course provides an introduction to mathematics, probability, and statistics graduate students need to know in order to do formal theoretical and quantitative empirical research in political science. These tools are crucial for analyzing data, describing theoretical and empirical relationships, and for understanding the logic of inference. After discussing the role of models in political science research, the first part of this course will focus on necessary mathematical topics such as functions, calculus, and algebra. Next, we turn to probability theory which provides a way of formally describing uncertainty. And then we finish this course with statistical inference which underlies the process of drawing inferences from the information contained in a sample of data.