Кто читает:: Департамент политологии и международных отношений

Статус:: Курс по выбору

Когда читается:: 1-й курс, 3, 4 модуль

Преподаватель

Желтоухова Анна Вячеславна

Full Syllabus

Abstract

This research seminar offers an overview of the key quantitative methods used in contemporary political science and helps students to master their use for their own research. It considers the basic concepts of statistics and probability. We also discuss such topics as exploratory data analysis and data visualization, statistical hypothesis testing, linear regression models, and regression diagnostics, generalized linear models, and the potential outcomes framework for causal inference. R programming language is used as a primary tool for data processing and statistical computations. Students are assumed to be familiar with high school math program, have basic computer literacy and be willing to work hard to learn the essentials of data analysis.

Learning Objectives

To acquaint students with statistical methods and terminology
To teach students how to implement statistical methods using R programming language.
To train students to independently develop a program and tools for conducting quantitative research

Expected Learning Outcomes

chooses statistical methods appropriate to his substantive research problem
designs a quantitative political study
reads (and understands) most academic PS articles
speaks the language of data fluently
uses R programming language for statistical computations

Course Contents

Design types, data types, and data summarization
Basic Statistical Concepts
Exploratory Data Analysis and Visualization
Inference and Hypothesis Testing
Simple Regression Methods
Confounding and Effect Modification (Interaction)
Multiple Regression Methods
Generalized Linear Models 1
Generalized Linear Models 2

Assessment Elements

Homework (1-5)
The most important aspects of assignments that affect grades are following: a) correctness of answers to questions given in an assignment, b) ability to write R code correctly (if necessary), c) appropriate use of statistical language, d) correctness of results’ interpretations. If all these criterions are met, you can expect an excellent grade (8-10 on 0-10 scale). Late assignments will be graded down by 1 point for each day of delay (but no more than 3 points in total). Plagiarism is prohibited.
In-class Participation
Midterm paper
The most important aspects of the paper to be graded are: 1) logical reasoning, 2) correctness and efficiency of R code written, 3) accuracy of statistical methods and models used, 4) correctness and creativity of results’ interpretation, 5) fluency and accuracy of statistical terminology used.
Final paper
The most important aspects of the paper to be graded are: 1) logical reasoning, 2) correctness and efficiency of R code written, 3) accuracy of statistical methods and models used, 4) correctness and creativity of results’ interpretation, 5) fluency and accuracy of statistical terminology used.

Interim Assessment

2021/2022 4th module
0.25 * Midterm paper + 0.25 * Homework (1-5) + 0.2 * In-class Participation + 0.3 * Final paper

Bibliography

Recommended Core Bibliography

Wilcox, R. R. (2016). Understanding and Applying Basic Statistical Methods Using R. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1237377

Recommended Additional Bibliography

Val Todd. (2017). Field and Iles (2016) An Adventure in Statistics: The Reality Enigma. PRISM, 1(1), 195–199. https://doi.org/10.24377/LJMU.prism.vol1iss1article304
Wickham, H., & Grolemund, G. (2016). R for Data Science : Import, Tidy, Transform, Visualize, and Model Data (Vol. First edition). Sebastopol, CA: Reilly - O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1440131

Магистерская программа «Сравнительная политика Евразии»

Контакты

Вконтакте

Международная аккредитация

Research Seminar "Quantitative Methods in Political Research"