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# Research Seminar "Quantitative Methods in Political Research"

2021/2022
Учебный год
ENG
Обучение ведется на английском языке
6
Кредиты
Статус:
Курс по выбору
Когда читается:
1-й курс, 3, 4 модуль

#### Преподаватель

Желтоухова Анна Вячеславна

### Course 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
• 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

#### 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