Political Methodology

Political Methodology is a basic component of modern Political Science. The OSU field in Political Methodology includes a wide variety of courses and related programs.


Jan Box-Steffensmeier, Bear Braumoeller, Skyler Cranmer, Marcus Kurtz, Chris Gelpi, William Minozzi, Tom Nelson, Jan Pierskalla, Amanda Robinson, Herb Weisberg (emeritus).

The statistical methodology courses that are offered on a yearly basis:

  • Math workshop for political science
  • Basic statistics
  • Linear and generalized linear models (regression analysis by OLS and MLE)
  • Causal inference
  • Machine learning

Qualitative Methods

Foundations of political analysis 
Introduction to Qualitative Methodology

We also offer, on a non-yearly basis and depending on instructor availability, more advanced courses in the following areas:

Courses in Research Design

Research Design
Questions in Survey Design
Experimental Methods
Survey Research Practicum

Additional advanced statistical courses

Time Series Analysis
Event History
Scaling and Dimensional Analysis
Bayesian Analysis
Computational Modeling
Cross-level Inference
Panel Data Analysis
Descriptive Network Analysis
Inferential Network Analysis
Text as Data

Additional Statistical Methods Courses

There are also several excellent statistical methods courses taught in the OSU Departments of Statistics, Economics, Sociology, Public Policy,and Psychology among others.

Related programs at OSU

PRISM: The Program In Statistics and Methodology and the related Political Research Laboratory
The OSU Graduate Interdisciplinary Specialization in Survey Research
ITV: The Interactive Television cooperative program with the Universities of Illinois, Minnesota, and Wisconsin, which provides regular access to a wide variety of advanced statistical courses
ICPSR: The Inter-university Consortium for Political and Social Research in Ann Arbor, including its Summer Program
Complexiy in Human, Natural, & Engineered Systems
Sante Fe Institute
Qualitative Research Methods

Graduate students can take Political Methodology as their major field, along with American Politics, Comparative Politics, International Relations, or Political Theory as their minor. Graduate students taking a minor in Political Methodology either can focus exclusively on statistical modeling or can take a combination of courses in statistical modeling, research design, and/or a special topics area. Additionally, students can take a joint minor in Political Methodology and Formal Theory. Political Methodology can also be taken jointly with Formal Theory as a major.

Recent Placements

Stony Brook University
Emory University
South Carolina University
Pennsylvania State University
University of Wisconsin
Michigan State University
University of Colorado - Boulder
George Washington University
JWAC - Joint Warfare Analysis Center
SSA - Social Science Automation
Nationwide Insurance

Minor/Major Programs

Minor: 4 classes for a minor (typically 1 per semester for the first 2 years and then students take the minor exam): 685/7551, 686/7552, 786/MLE/7553 and then either an advanced course or 684/7780.

Major: 5 classes, where at least two are advanced beyond 786/MLE/7553 (so if students also take 684/7780, then 6 classes). These additional courses can and likely will be taken beyond the second year.

Course descriptions to better convey what we want to teach and what understandings we want for the students from the first year sequence. The goal is to also have better continuity across courses. This will allow us to communicate to the other subfields what we are providing and teaching their students.

685/7551: This course is designed for Political Science graduate students intending to do empirical research. It introduces students to methods for constructing simple empirical representations of social science theories and for rigorously testing those theories with data. We focus on four topics, beginning with the logics of empirical analysis; descriptive statistics and the basic linear model; probability and statistics; and statistical inference. The course will emphasize fundamental statistical concepts as well as their practical application and will draw examples from a range of substantive subfields in Political Science. Topics include random variables, basic hypothesis testing, BLUE, regression and assumptions. This course is designed for students with little or no formal training in statistics or in the analysis of social science data. There are no prerequisites, though it is assumed that students have the equivalent of college algebra and will have taken our department’s summer math camp. Upon completion of this course, students will be able to read and critically evaluate empirical political science research; will have sufficient background and experience to formulate and test simple empirical representations of social science theories; and will have a solid statistical background needed for more advanced methodological training. The course also provides work with statistical software, such as Stata or R.

686/7550: The course covers all core elements of OLS regression: bivariate and multivariate regression analysis, interaction effects, hypothesis testing, and violations of OLS assumptions. The aim of the course is to explore the statistical background of OLS in combination with its empirical application. Topics include regression, hypothesis testing, functional form, diagnostics, heteroskedasticity, autocorrelation, endogeneity, introduction to dichotomous dependent variables and other MLE topics. The course also provides work with statistical software, such as Stata or R.

The Ph.D. Candidacy Examination

To demonstrate mastery of the field, students are required to pass a Candidacy Examination. There is both a written and an oral component to the Candidacy Examination. There is an 8 hour written exam for the both the major and minor. A paper is required for the major after the 3rd year.