• A
• A
• A
• ABC
• ABC
• ABC
• А
• А
• А
• А
• А
Regular version of the site
Bachelor 2019/2020

## Quantitative Methods of Political Research

Type: Elective course (Political Science and World Politics)
Area of studies: Political Science
When: 2 year, 3, 4 module
Mode of studies: offline
Instructors: Aleksei Sorbale
Language: English
ECTS credits: 5

### Course Syllabus

#### Abstract

This discipline refers to the professional cycle, the basic part of the profile. The study of this discipline is based on the following disciplines: Mathematics and Statistics, Comparative Politics, Research Seminar (first and second years). The main provisions of the discipline can be used in the preparation of term papers and BA diplomas. As a result of mastering the course, students will get an idea of ​​the heuristic abilities of quantitative methods of daat analysis in political studies; increase the skills necessary for collecting quantitative data and visualizing them, comparing various samples using statistical tests, studying quantitative data with basic statistical tools; gain the knowledge necessary to work with specialized statistical programs, in particular, with the statistical environment R. #### Learning Objectives

• form the understanding of the cognitive abilities of quantitative methods of data analysis in political science research
• promote knowledge and skills necessary for collecting quantitative data and its visualization; comparison of different data sets using statistical tests; study the relationships within quantitative data with the help of basic statistical tools
• promote skills necessary to work with specialized statistical programs, in particular, with the statistical environment R #### Expected Learning Outcomes

• Understands the structure of the course and forms of control, basic terms and concepts of statistics
• Understands the functions of descriptive statistics in a study with quantitative design.
• Able to apply the heuristic capabilities of the statistical program R to obtain descriptive statistics.
• Understands the role of visualization in a study with quantitative design.
• Able to apply the heuristic capabilities of statistical program R for data visualization.
• Understands the types and meaning of statistical hypotheses and errors.
• Able to apply the heuristic capabilities of the statistical program R to test statistical hypotheses and the presence of statistical errors.
• Understands the meaning of chi-square (X2) in a study with quantitative design.
• Able to apply the heuristic capabilities of the statistical program R to calculate the chi-square (X2).
• Understands the significance of statistical tests in a study with quantitative design.
• Understands the essential differences between statistical tests.
• Able to apply the heuristic capabilities of the statistical program R for statistical tests.
• Understands the significance of the Mann-Whitney test in a study with quantitative design.
• Understands the essential differences between the Mann-Whitney test and other statistical tests.
• Able to apply the heuristic capabilities of the statistical program R for the Mann-Whitney test.
• Understands the meaning and function of correlation in research with quantitative design.
• Able to apply the heuristic capabilities of the statistical program R to calculate the correlation coefficient.
• Understands the role of paired linear regression in a study with quantitative design.
• Able to apply the heuristic capabilities of the statistical program R for paired linear regression.
• Understands the importance of OLS regression in a study with quantitative design.
• Understands the principles of OLS regression.
• Able to apply the heuristic capabilities of the statistical program R for OLS regression.
• Understands the importance of conducting OLS regression models.
• Understands the essence of technical problems and preconditions for conducting OLS regression.
• Able to apply the heuristic capabilities of statistical program R to check the OLS regression for technical problems.
• Able to apply the heuristic capabilities of the statistical program R for the diagnosis of OLS regression models.
• Understands the essence of the substantive problems of OLS regression.
• Able to apply the heuristic capabilities of the statistical program R to check OLS regression for substantive problems.
• Understands the importance of logistic regression for a study with quantitative design.
• Able to apply the heuristic capabilities of the statistical program R for conducting logistic regression.
• Understands the importance of ordinal logistic regression for a study with quantitative design. #### Course Contents

• Introduction to the discipline: basic concepts and R basics
• Descriptive statistics
• Data Visualization: Principles, Tools, Examples
• Statistical hypotheses and errors
• Statistics and chi square (x2)
• Statistical tests: binominal, t test, Mann Whitney test
• Statistical tests: Mann Whitney test
• Correlation
• Paired linear regression
• Multiple OLS regression: principle, interpretation, design
• OLS regression diagnostics
• “Technical” problems and prerequisites for OLS regression
• Substantive problems of regression models
• Logistic regression
• Ordered Logistic Regression (Overview). Course Summary #### Assessment Elements

• Seminar participation
• Practical homework
• Test
• Exam
Экзамен проводится в устной форме. Экзамен проводится на платформе Zoom (https://zoom.us/). К экзамену необходимо подключиться за 10 минут до начала. На платформе Zoom предусмотрен тестирование системы. Компьютер студента должен удовлетворять требованиям: работающая камера и микрофон. Для участия в экзамене студент обязан: включить камеру и микрофон, подтвердить личность. Во время экзамена студентам запрещено: общаться (в социальных сетях, с людьми в комнате), списывать, использовать дополнительные девайсы и средства связи, кроме компьютера. Во время экзамена студентам разрешено: пользоваться собственными письменными конспектами (в тетради или на распечатанных листах). Кратковременным нарушением связи во время экзамена считается прерывание связи до 3 минут. Долговременным нарушением связи во время экзамена считается прерывание связи на 3 минуты и более. При долговременном нарушении связи студент не может продолжить участие в экзамене. Процедура пересдачи аналогична процедуре сдачи. #### Interim Assessment

• Interim assessment (4 module)
0.3 * Exam + 0.2 * Practical homework + 0.2 * Seminar participation + 0.3 * Test 