Quantitative Methods of Political Research

2025/2026

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Political Science and International Affairs

Course type:

Elective course

When:

1 year, 3 module

Instructor

Starodubtsev, Andrey

Course Syllabus

Abstract

The course is designed for the first-year MA "Comparative Politics of Eurasia" students introducing basic and more advanced concepts and methods of quantitative political science. It aims at familiarising the students with nuts and bolts of statistical analysis and its application to various research problems in political science. It covers a variety of identification strategies (from linear regression to time-series) with examples from existing scholarship. The course requires a modest degree of prior familiarity with the qualitative methods and statistics.

Learning Objectives

• Learning the basic statistical skills necessary to conduct quantitative political study
• Developing the programming skills in the R software.
• Conducting quantitative analysis on the topic of student's choice.

Expected Learning Outcomes

• - Knows the basic concepts of statistical inference including probability theory, variable types, and distributions.
• - Knows about the core approaches to statistical inference (maximum likelihood, frequentist, and Bayesian) and its assumptions.
• - Is able to read and understand the papers using quantitative methods, assess the validity of the results and critically evaluate the findings.
• - Is able to produce their own quantitative research projects in accordance with replicability and transparency standards.
• - Is capable of using R to work with statistical tools (e.g. visualise the distributions, estimate the key quantities of interest, use simulations etc.).

Course Contents

• Main Concepts of Statistical Inference
• OLS models
• Quality of model fit
• Generalized Linear Models
• Panel Data

Assessment Elements

• Home assigments
  Intermediate semester work on solving one of the problems related to the social sciences with the help of programming. Based on the materials of past seminars.
• Final Project
  A project requires students to look for a data source and conduct its preliminary analysis to answer relevant research questions using course materials
• In-class activity

Interim Assessment

• 2025/2026 3rd module
  0.4 * Final Project + 0.4 * Home assigments + 0.2 * In-class activity

Bibliography

Recommended Core Bibliography

• Regression and other stories, Gelman, A., 2021

Recommended Additional Bibliography

• The essentials of political analysis, Pollock III, P. H., 2016

Authors

• BARYKIN IAROSLAV ANDREEVICH