Kosuke Imai's Teaching

POL 502: Mathematics for Political Science

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 and handouts.

Pol 571: Quantitative Analysis I

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 first half of the course will be devoted to probability theory, which serves as a foundation of statistical theory. The second half 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 statistical programming as well as basic principles of probability theory and statistical inference. This course assumes the mathematical knowledge taught in POL 502, and prepares students for the next course in the sequence, POL 572. Download the syllabus and handouts.

POL 572: Quantitative Analysis II

This course is the second course in applied statistical methods for social scientists. Students will learn a variety of statistical methods including models for causal inference, discrete choice models, duration (or hazard) models, event count models, multiple equation models, 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 levels of POL 502 and 571, and prepares students for the final course of the sequence, POL 573. Download the syllabus.

Pol 573/Soc 595: Quantitative Analysis III: Applied Bayesian Data Analysis

Note: During Spring 2008, the focus of this course will be statistical methods for causal inference rather than applied Bayesian statistics, which may be taught during the academic year 2008-2009. Download the syllabus.

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.

POL 722: Probability and Statistics

This course presents basic principles of mathematical probability and statistics that are essential for advanced quantitative analysis in political science research. The first half of the course will cover basic probability theory, which serves as a foundation of statistical theory. The second half will be devoted to topics for statistical inference, which include estimation, hypothesis testing, asymptotic analysis and regression. Students are expected to complete twelve problem sets, one for each topic, each of which consists of four or five exercises.

POL 451: Statistical Methods in Political Science

In this course, students will learn basic research design and data analysis methodology in empirical social science research. The main goal is to learn how statistical theory can be used to make causal inferences in experimental and observational studies. The course satisfies the analytical methods requirement for politics majors. The materials of this course are particularly useful for those who plan to use quantitative analysis in their junior papers and senior thesis as well as for those who wish to apply for graduate programs in the social sciences. Familiarity with elementary probability theory is helpful, but is not required. Download the syllabus.