Graduate Seminars Spring 2021

PL SC 503

Multivariate Analysis for Political Research

Professor Christopher Zorn

This is the second (full) course in quantitative methods in Penn State's political science Ph.D. program. The course introduces students to regression-type models for the analysis of quantitative data and provides a basis of knowledge for more advanced statistical methods. The course assumes basic math literacy, including familiarity with probability theory, properties of estimators, rudimentary calculus, and linear algebra. The bulk of the course will focus on general models of the form Y = f(XB) + e, and will include discussions of the mathematical bases for such models, their estimation and interpretation, model assumptions and techniques for addressing violations of those assumptions, and topics related to model specification and functional forms. Under this general framework, we will also provide a very brief overview of regression models for binary, ordered, unordered, and event count variables.

 Wednesdays, 9:00 a.m. – 12:00 p.m.



PL SC 506

Game Theory Part I

Professor Sona Golder

Game theory is a mathematical tool used to study strategic interaction between two or more decision makers that have an effect on each others’ outcomes. Political scientists are increasingly using game theory to analyze strategic interactions across many different political settings. For example, international relations scholars often use game theory to explain when wars are more likely to occur. To study electoral competition, political scientists employ the tools of game theory to analyze how policy platforms selected strategically by political candidates influence electoral outcomes. This course aims to give students an entry-level understanding of the basic concepts of game theory, and how these concepts have been applied to the study of political phenomena. Students should leave the course with a working knowledge of games of complete and incomplete information, to the point where they can state a model correctly, solve it, and elucidate some of the theory's empirical implications.

 Tuesdays, 1:30 p.m. – 4:30 p.m.



PLSC 511

Professional Norms in Political Science

Professor Vineeta Yadav

This course has three main related goals. The first is to help you get the most out of your graduate school experience. The second is to help prepare you for becoming an academic by improving your understanding of the profession. The third is to prepare you to be an effective and engaged teacher. To accomplish these goals, we will discuss how to make the most of the graduate school experience to make your job portfolio is as strong as it can be. We will learn how to be an effective teacher and mentor inside and outside of the classroom by developing effective syllabi, preparing to teach diverse student populations, and tailoring class sections to meet student needs. Other topics will include diversity in the profession, strategies for effective conference attendance, and the responsible conduct of research.

Students will be expected to attend each and every session, participate in seminar discussions, and complete weekly assignments. Grading for the course will be pass/fail.

 Note: You should enroll in this course if you are entering the second semester of your first year. This is a required, 1.5 credit course.

Mondays, 3:00 p.m. – 4:30 p.m.



  PLSC 518

Survey Design II

Professor Eric Plutzer

 Survey methodology is concerned with techniques designed to collect data by (a) asking people questions, and (b) aggregating those answers in ways that generate valid and reliable inferences about a population of individuals.  This course, one of two courses that introduce survey methodology to students, is primarily concerned with the science of collecting data (while PLSC/SOC 519 is primarily concerned with analyzing data).  Topics will include: Sample recruitment and panel study retention, Questionnaire design, Essential features of collecting data via face-to-face interviews, by live telephone interviewers, by pencil and paper questionnaires, and by surveys conducted via internet and mobile technologies.

 Mondays, 6:00 p.m. – 9:00 p.m.



PLSC 550

Comparative Political – Theory and Methodology

Professor Gretchen Casper

This course is the core seminar for the field of comparative politics in the political science Ph.D. program.  It provides an introduction to the dominant questions, theories, and empirical research in comparative politics.  The substantive topics covered in the class include democracy and dictatorship, democratic performance, political institutions, culture and identity issues, elections and political parties, representation and accountability, and political economy.  The course has two goals: (i) to prepare students for a research career in comparative politics by providing a general survey of the field and (ii) to help prepare graduate students for the comprehensive examination in comparative politics.

Thursdays, 9:00 a.m. – 12:00 p.m.

265 Willard Building


PLSC 597.001

Political Geography

Professor Xun Cao

Students of various social sciences disciplines such as economics, sociology, and political science have long been interested in understanding the role of geography in shaping processes as diverse as economic development, civil conflict, and social movement. Theoretically, studying the impacts of geography implies the introduction of a new dimension to the study of political and economic processes. Many new questions need to be answered, for instance, what is the relationship between geography and collective action? Does geography shape voters’ preferences? What are the mechanisms that underpin specific geographical patterns of economic development, unemployment, and inequality? Whether and how geography affects changes of ethnic conflicts? Such questions require new theoretical models and empirical methodologies, and often geo-coded data that take into account spatial interdependences. This course will lay out some conceptual and methodological foundations drawn from existing studies of political geography. We will focus on the origins of geographical patterns of development and economic growth. We will also analyze the role of geography in shaping individual preferences and incentives to engage in politics, and how such micro-level factors are aggregated to shape macro-level outcomes such as state building and civil war. We will also introduce students to some simple applications of GIS data and methodologies and related software packages that can be used to model spatial processes.

Thursdays, 6:00 p.m. – 9:00 p.m.



PLSC 597.002

Seminar on Machine Learning

Professor Bruce Desmarais

Political science research is now regularly conducted using data that is larger and more complex than the data for which conventional statistical tools were designed. Examples of such data include population-scale information on individual-level consumer and political behavior, data streams collected from social media, and archives of electronic government records.  There are three fundamental ways in which fine-grained, voluminous, and high-dimensional data require a set of methods that are more flexible than the conventional toolkit of quantitative social science. First, the data is inherently more complex, making it difficult to specify an adequate statistical model from theory alone. Second, the data is high dimensional, meaning there are more variables than one can include in conventional statistical models. Third, the data contains adequate information to make accurate predictions about unseen data (e.g., forecasts). These three features demand a statistical toolkit that is capable of learning model structure, selecting variables, and producing accurate predictions, which are all capabilities of foundational machine learning methods. In this course, we will cover foundational machine learning, with a focus on application to problems in political science.  

Tuesdays, 9:00 a.m. – 12:00 p.m.



PLSC/AFAM 597.003

Seminar on Comparative Racial & Ethnic Politics

Professor Candis Smith

Given that race and ethnicity can be understood as (a) socially constructed categories and (b) ideologies that allow for the unequal distribution of rights, material goods, and privileges, it becomes necessary to understand how states/governments take part in shaping racial/ethnic categories and the ideologies that prop them up. This course centers the role of governments, politics, and policy in shaping how notions of race and ethnic become “commonsense” in countries across the globe as well as how these concepts serve to diminish, enhance, or constrain the privileges of citizenship.

Mondays, 9:05 a.m. – 12:05 p.m.

371 Willard Building


SoDA 501

Big Social Data: Approaches and Issue

Professor Burt Monroe

Interdisciplinary integration of computational, informational, statistical, visual analytic, and social scientific approaches to the creation of big social data. This course addresses computational, informational, statistical, visual analytic, and social scientific approaches to the creation of data that are both "social" (about, or arising from, human interactions) and big (of sufficient scale, variety, or complexity to strain the informational, computational, or cognitive limits of conventional social scientific approaches to data collection or analysis). Examples include text, image, audio, video, intensive spatial and/or longitudinal data, data with complex network, hierarchical and/or other relational information, data from distributed sensors and mobile devices, digitized archival data, and data exhaust from sources like social media. Possible topics include sources of social data, data structures and formats for social data, data collection and manipulation technologies, data linkage and alignment, ethics and scientific responsibility in human subjects research, experimental and observational data collection design for causal inference, measurement of latent social concepts, reliability and validity, search and information retrieval, nonrelational and distributed databases, and standards for data preservation and sharing.

Thursdays, 1:30 p.m. – 4:30 p.m.