Courses

Overview

The core faculty of PML run the Models and Methods (M&M) field for the political science Ph.D. program at MIT. We teach various courses in the field, both for students who choose M&M as their first or second major field and for students who simply want to acquire advanced quantitative skills for their substantive empirical research. We also offer courses at the undergraduate level.

Our graduate course offerings are centered around the four-course Quantitative Research Methods sequence, which is normally taken while a student is in their first and second years of their graduate study. The Quant Sequence is supplemented by the two Math Camps which occur towards the end of summer. The sequence is designed to get students up to speed with the cutting-edge quantitative empirical research in political science and also to prepare them to become first-rate political methodologists. 

Other graduate courses include the Formal Theory class, as well as seminar classes focused on the intersections of quantitative methodology and major substative areas of political science, such as political economy and international relations.


Graduate Courses

17.8XX Math Camp I

The Math Prefesher is designed to introduce and review core mathematics and probability prerequisites that you will need to be successful in the quantitative methods courses in the Political Science department and elsewhere at MIT. In an intense one-week course, we will cover key concepts from calculus, linear algebra, probability theory, and an introduction to statistical computing. The learning will proceed through lectures, hands-on exercises, and homework. The aim of the course is to give you an opportunity to practice some of the mathematics you may have previously learned and to introduce you to areas that may be new to you so that you will be ready to enter classes that presume prior familiarity with these concepts, such as 17.800 Quantitative Research Methods I.  Syllabus

17.800 Quantitative Research Methods I: Regression

Graduate level introduction to statistical methods for political science and public policy research, with a focus on linear regression. Teaches students how to apply multiple regression models as used in much of political science and public policy research. Also covers fundamentals of probability and sampling theory. Syllabus.

17.802 Quantitative Research Methods II: Causal Inference

Survey of advanced empirical tools for political science and public policy research with a focus on statistical methods for causal inference, i.e. methods designed to address research questions that concern the impact of some potential cause (e.g., an intervention, a change in institutions, economic conditions, or policies) on some outcome (e.g., vote choice, income, election results, levels of violence). Covers a variety of causal inference designs, including experiments, matching, regression, panel methods, difference-in-differences, synthetic control methods, instrumental variable estimation, regression discontinuity designs, quantile regressions, and bounds. Syllabus.

17.8XX Math Camp II

The math camp will prepare students to take Quant III and Quant IV as well as other advance classes in political methodology. The goal of the class will be to remind students of basic and intermediate mathematical concepts that are useful for Quant III and Quant IV and increase both mathematical fluency and problem solving ability. I will also try to give some programming tools that you may find useful when solving problem sets of Quant III. The prerequisites include Quant I and Quant II. Syllabus.

17.804: Quantitative Research Methods III: Generalized Linear Models and Extensions

This course is the third course in the quantitative research methods sequence at the MIT political science department. Building on the first two courses of the sequence (17.800 and 17.802), this class covers advanced statistical tools for empirical analysis in modern political science. Our focus in this course will be on techniques for model-based inference, including various regression models for cross-section data (e.g., binary outcome models, discrete choice models, sample selection models, event count models, survival outcome models, etc.) as well as grouped data (e.g., mixed effects models and hierarchical models). This complements the methods for design-based inference primarily covered in the previous course of the sequence. This course also covers basics of the fundamental statistical principles underlying these models (e.g., maximum likelihood theory, theory of generalized linear models, Bayesian statistics) as well as a variety of estimation techniques (e.g., numerical optimization, bootstrap, Markov chain Monte Carlo). The ultimate goal of this course is to provide students with adequate methodological skills for conducting cutting-edge empirical research in their own fields of substantive interest.  Syllabus.

17.806: Quantitative Research Methods IV: Advanced Topics 

This course is the fourth and final course in the quantitative methods sequence at the MIT political science department. The course covers various advanced topics in applied statistics, including those that have only recently been developed in the methodological literature and are yet to be widely applied in political science. The topics for this year are organized into three broad areas: (1) research computing, where we introduce various techniques for automated data collection, visualization, and analysis of massive datasets; (2) statistical learning, where we provide an overview of machine learning algorithms for predictive and descriptive inference; and (3) finite mixture models (e.g., Latent Dirichlet allocation for text analysis), as well as a variety of estimation techniques such as EM Algorithm and Variational Inference.  Syllabus.

17.810: Game Theory and Political Theory

This course provides an introduction to formal theoretical analysis in political science. This course is designed as a rigorous introduction to the concepts and models used to analyze political behavior in strategic contexts. The course focuses on non-cooperative game theory covering normal and extensive form games, games of incomplete information, repeated games, and bargaining. Qualified undergraduates can also take the course.  Syllabus.

17.830: Empirical Methods in Political Economy

This course surveys recent quantitative work in political economy. Unlike a typical graduate level course in political science, we will focus on a limited number of readings each week, with the goal of understanding and evaluating in detail all the analytical decisions made by the authors of each study. Topics range from the link between institutions and political development in poor societies to the operation of legislatures in rich democracies. Methodological topics that will be covered include panel methods, the use of behavioral measures in experiments, statistical learning models, measurement models, estimating spillover effects, and text analysis. Syllabus.

17.426: Empirical Models in International Relations

This course explores statistical methods as applied to international relations, with  reference to similar  applications in comparative politics and other fields . We will discuss  statistical approaches to analyzing  various  types  of  data used  by  IR  scholars.    We  will  read  both  methodological  and  applied  work,  familiarizing students with an array of models  and critically analyzing their strengths and weaknesses.  It  is  not  intended  as  a  substitute  for  Quantitative  Methods  I,  II,  and  III ,  but  as  a  complementary  course. The goal of the course is to expose students to the range of quantitative models applied in  international relations scholarship, assess the strengths and weaknesses of particular modeling choices,  and  to  develop  the  ability  to  design  empirical  research  projects  of  their  own.  It  is  strongly  recommended that students have taken Quantitative Methods I prior to this course.  Syllabus

17.850: Political Science Scope and Methods (Graduate)

The world is full of compelling stories, fascinating events, and baffling puzzles. But how do  these ideas translate into research? The purpose of this course is to help you move from  topics of interest to research questions, and to give you the skills necessary to answer those  questions with solid, well- designed empirical research. The course draws on current research  in political science to introduce you to the enterprise of scientific research in politics.  Specifically, the course reviews the basic principles of research design and eval uates the  strengths and weaknesses of various empirical approaches. Mastering these skills —indeed  internalizing them so that they become second nature —is one of the most important things  that you will learn in graduate school. You will emerge from this course not only a more  sophisticated consumer of the literature, but in a position to design and conduct your own  independent scholarly research. Syllabus

17.878: Qual Methods and Fieldwork

This course is intended for political science PhD students, though we will also be drawing on sociology and anthropology. By the end of the course, students should be well-equipped to undertake their own fieldwork. Students will also be familiar with the major debates surrounding qualitative research in the discipline, and they will be able to confidently assess the design, execution, and interpretation of qualitative field research. The course focuses especially on ethnography.  Syllabus.


Undergraduate Courses

17.801: Political Science Scope and Methods (Undergraduate)

This course introduces principles of empirical and theoretical analysis in political science through research projects currently conducted in the department. Introduces students to major research questions in political science - and to different ways of examining those questions. Emphasizes how this research in progress relates to larger themes, and how researchers confront obstacles to inference in political science. Includes substantial instruction and practice in writing (with revision) and oral presentations.

17.803: Political Science Laboratory

This class introduces undergraduate political scientists to the basic quantitative tools of political science research. In particular, this class explores the key statistical and computational research tools that social scientists use to frame and answer empirical questions. When you finish this subject successfully, you will be able to conduct quantitative research, be better able to read critically much of the professional literature in political science and other statistically-based fields, and have an employable skill. The most important purpose behind the Political Science Laboratory, however, is to help you move from a passive reader of social scientific tomes to a creative producer of new insights.

A particular focus of the class will be on the issue of causal inference. The political world  is composed of a web of cause-and-effect relationships that are entangled and intertwined. The complex nature of our world makes our life as political scientists tough and challenging, even compared to those of rocket scientists and nuclear physicists. The central theme that runs throughout  the course will be: How can we tell causation from mere association? The answer lies in good research designs and appropriate statistical tools, as you will learn by the end of the semester.

This class emphasizes practical skills and intuition for good quantitative social science, compared to traditional statistics courses. As such, the class will involve lots of hands-on exercises, lab sessions, group work, discussion and presentation sessions, along with more traditional problem sets. Throughout the semester, you will also work on an original research project that involves data collection, analysis with a statistical computing language R), and a final write-up of your findings. Syllabus.

17.811: Game Theory and Political Theory

This course provides an introduction to formal theoretical analysis in political science. This course is designed as a rigorous introduction to the concepts and models used to analyze political behavior in strategic contexts. The course focuses on non-cooperative game theory covering normal and extensive form games, games of incomplete information, repeated games, and bargaining. Qualified undergraduates can also take the course.  Syllabus.

17.831: Data and Politics 

In this course, students will both learn how statistics are changing elections and how to use statistics to analyze political data. While the substantive focus will be on elections, the principles and methods learned in this course have broad applicability to the decisionmaking in a broad variety of fields. The course will have 3 modules organized around a different methodological topic, with an application to an electoral phenomenon. For each module, students will work with the professor on analyzing a unique dataset related to electoral politics. The first module will involve the analysis of survey data on electoral behavior. The second module will focus on the design and implementation of original experiments in order to study political attitudes. The third module will use statistical models to predict electoral behavior using large datasets. Syllabus.

17.835 Machine Learning and Data Science in Politics 

Empirical studies in political science is entering a new era of “Big Data” where a diverse range of data sources have become available to researchers. Examples include network data from political campaigns, data from social media generated by individuals, campaign contribution and lobbying expenditure made by firms and individuals, and massive amount of international trade flows data. How can we take advantage of these new data sources and improve our understanding of politics? This course introduces various machine learning methods and their applications in political science research. Syllabus.