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Pol 502:
Mathematics for Political Science (Fall 2003; Fall 2005)
This course presents basic mathematical concepts that are essential for formal and quantitative analysis in political science research. It prepares students for advanced graduate courses offered in the department (e.g., POL 571-573, 575-576). The topics include real analysis, linear algebra, and probability theory. There is no prerequisite. The course is aimed for both students with little prior exposure to mathematics and those who have taken some courses in the past but wish to gain a more solid foundation. Undergraduate students who want to do the graduate-level coursework in quantitative methods can also take the course for credit. Download the syllabus. |
Pol 571:
Quantitative Analysis I (Spring 2006)
This course is the first course in applied statistical methods for social scientists. Students will learn how statistical methods can be used to conduct causal inferences, exploratory data analysis, forecasting, and hypothesis testing. The course covers the linear model in some depth and if time permits also introduces generalized linear models. An emphasis of the course is given to practical data analysis, and students will learn elementary statistical programming as well as basic principles of statistical inference. This course assumes the mathematical knowledge taught in POL 502, and prepares students for the next course in the sequence, POL 572. |
Pol 572:
Quantitative Analysis II (Fall 2005)
This course is the second course in applied statistical methods for social scientists. Students will learn a variety of statistical methods including discrete choice models, duration (or hazard) models, event count models, multiple equation models, time-series and time-series cross section models, panel data models, and others. The methods for analyzing sample surveys and randomized experiments are also covered. The models and methods are introduced in the context of practical data analysis, and the emphasis is given to the estimation of quantities of interest given one's scientific research question. The course also provides the overview of both classical and Bayesian inferences (and their connections) as well as various other modes of statistical inference. This course assumes the knowledge of materials taught at the level of POL 571, and prepares students for the final course of the sequence, POL 573. |
Pol 573/Soc 576:
Quantitative Analysis III: Applied Bayesian Data Analysis (Spring 2004; Spring 2005)
I am not teaching this course during the academic year of 2005-2006. In this course, students will learn a variety of statistical methods used in empirical social science research. The course covers the basics of applied Bayesian data analysis and a variety of applications. We adopt a Bayesian approach because it provides a general and flexible framework for applied statistical modeling. The main goals of the course are that after taking it, students can understand and implement advanced statistical models in order to answer their own research question. The course provides essential data analysis tools for your dissertation and future empirical research. Download the syllabus. |
Pol 451:
Statistical Methods in Political Science (Spring 2005)
In this course, students will learn how to analyze data in order to test empirical hypotheses in their own research. We will cover the basics of probability and statistical theory and assess the validity of existing studies. One main goal of the course is to learn how statistical theory can help us make causal inferences using experimental and observational data. Other applications include survey sampling and forecasting. Download the syllabus. |