Бакалавриат
2026/2027
Научно-исследовательский семинар "Подготовка и написание курсовой работы"
Статус:
Курс обязательный (Международная программа «Международные отношения и глобальные исследования»)
Кто читает:
Факультет мировой экономики и мировой политики
Где читается:
Факультет мировой экономики и мировой политики
Когда читается:
3-й курс, 1-3 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Контактные часы:
36
Course Syllabus
Abstract
This research seminar is set to help students in their work on individual research projects leading to term paper, by refreshing knowledge and improving skills needed for selecting adequate research strategy and developing appropriate research design. During the research seminar, students will be able to practice specific methods fitting their research aims/questions by discussing their peculiarities and developing their own research projects. Moreover, the research seminar will consider machine learning techniques that could be used for academic research on key issues in international relations and public policy, including decision trees, gradient boosting, neural networks, etc. The course will also offer ready-made AI tools, developed using machine learning methods and neural networks, to collect and analyse relevant literature.
Learning Objectives
- to develop students' skills in designing, conducting, and validating research by teaching them how to formulate research questions, select appropriate methodologies, collect and analyze data, assess the validity and reliability of their findings, and apply ethical standards throughout the research process.
- To prepare students for advanced research projects or theses in their academic and professional careers by equipping them with the necessary skills to design robust research proposals, conduct comprehensive literature reviews, apply appropriate research methodologies, analyze data effectively, adhere to ethical standards, and present their findings clearly and persuasively.
Expected Learning Outcomes
- Identify the appropriate research scenarios where regression analysis adds value over simpler methods like correlation or t-tests.
- Distinguish between prediction-oriented and explanation-oriented uses of regression, and apply the right interpretive framework for each.
- Evaluate whether the key assumptions of linear regression are met in a given dataset, and recognize when alternative approaches may be needed.
- Formulate precise, testable hypotheses from broad research questions using clear directional or non-directional statements.
- Operationalize abstract theoretical constructs into measurable independent and dependent variables with appropriate scales of measurement.
- Match their research design to the correct regression model (linear, logistic, or multivariate) and justify that choice with logical and methodological rigor.
- Interpret regression coefficients (slope and intercept) in substantive, non-technical terms relevant to their field.
- Generate point predictions and prediction intervals from a fitted regression equation for new observations.
- Control for confounding variables by adding relevant predictors and interpret how coefficients shift when new variables enter the model.
- Compare nested models using F-tests, adjusted R-squared, and information criteria (AIC/BIC) to determine whether additional predictors meaningfully improve fit.
Course Contents
- Introduction to the main philosophy, principles, and methods of scientific research
- Discussion of academic standards, ethics, and validity of research
- Research topic selection and initial steps of the research
- Literature review and critical thinking
- Data collection and data analysis
- Introduction to Regression Analysis: Why and When Do We Use Regression?
- From Theory to Variables: Research Questions, Hypotheses, and Regression Models
- Simple Linear Regression: Coefficients, Predictions, and Model Fit
- Multiple Regression: Controls and the Logic of Comparing Models
- From Research Question to Regression Results: Mini Empirical Research Workshop
- Categorical Variables and Dummy Variables
- Interaction Effects: When Does the Effect Depend on Something Else?
- Time-Series and Panel Data: Studying Countries, People, and Organizations Over Time
- Fixed Effects and Random Effects in Panel Data
- Reading and Interpreting Regression Tables in Academic Research
- Final part of the block
Assessment Elements
- Oral examStudents will be required to answer three questions. All questions will be directly related to seminars, projects (two in total: one quantitative and one qualitative) as well as to you research (methodological design, literature review, etc.).
- Presentation of interim results (based on individual research projects)Analysis of relevant literature and data, research problem, research relevance, research question, objectives and tasks, hypothesis, theoretical methods, plan and structure of the work.
- Seminar Participation (in discussions and debates)
Interim Assessment
- 2026/2027 1st module0.8 * Presentation of interim results (based on individual research projects) + 0.2 * Seminar Participation (in discussions and debates)
- 2026/2027 3rd module0.35 * Presentation of interim results (based on individual research projects) + 0.4 * Oral exam + 0.25 * Seminar Participation (in discussions and debates)
Bibliography
Recommended Core Bibliography
- A student's guide to methodology : justifying enquiry, Clough, P., 2008
- Cerutti, F. (2017). Conceptualizing Politics : An Introduction to Political Philosophy. Abingdon, Oxon: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1511262
- Dinesh S. Hegde. Essays on Research Methodology [Электронный ресурс]- Springer India 2015. Online ISBN 978-81-322-2214-9. Режим доступа: https://link.springer.com/content/pdf/10.1007%2F978-81-322-2214-9.pdf
- Linear regression analysis, Seber, G. A. F., 2003
- Linear regression models. Applications in R, Hoffman, J. P., 2022
- Nonlinear regression, Seber, G. A. F., 2003
- Statistical tools for nonlinear regression : a practical guide with S-PLUS and R examples, Huet, S., 2010
- Регрессия: теория и практика : с примерами на R и Stan, Гельман, Э., 2022
Recommended Additional Bibliography
- Holden, M. T., & Lynch, P. (2004). Choosing the Appropriate Methodology: Understanding Research Philosophy. Marketing Review, 4(4), 397–409. https://doi.org/10.1362/1469347042772428