31402
Grundkurs
Introduction to Quantitative Methods in Social Sciences
Victor Rudakov
Kommentar
The course is designed for students with a background in social sciences or the humanities who wish to develop their skills in quantitative data analysis. It is demanding but could be an excellent choice if you have always wanted to learn quantitative methods and apply them in your thesis, even with little prior experience. During the course, we will focus in particular on the application of regression analysis in social science research, including its underlying assumptions, limitations, and the use of binary and multiple-choice models (e.g., logit and probit). The concepts of regression analysis will be explained in clear and accessible language, using real data and research examples from Economics, Sociology, and Political Science.
The course consists of two parts. In the first, lecture-style block, we will cover the key concepts and methods necessary for the practical application of quantitative techniques. In the second part, we will work together on applying these methods to real empirical data. The course will be supported by hands-on exercises in Stata, including an introductory session on Stata programming. Prior knowledge of statistics or Stata is an advantage but not required, as the course is designed for beginners. Students are required to complete several assignments and tests based on empirical data analysis and lecture content. To pass the course, students must score at least 60% on two tests. Schließen
16 Termine
Regelmäßige Termine der Lehrveranstaltung
Do, 16.10.2025 10:00 - 12:00
Do, 23.10.2025 10:00 - 12:00
Do, 30.10.2025 10:00 - 12:00
Do, 06.11.2025 10:00 - 12:00
Do, 13.11.2025 10:00 - 12:00
Do, 20.11.2025 10:00 - 12:00
Do, 27.11.2025 10:00 - 12:00
Do, 04.12.2025 10:00 - 12:00
Do, 11.12.2025 10:00 - 12:00
Do, 18.12.2025 10:00 - 12:00
Do, 08.01.2026 10:00 - 12:00
Do, 15.01.2026 10:00 - 12:00
Do, 22.01.2026 10:00 - 12:00
Do, 29.01.2026 10:00 - 12:00
Do, 05.02.2026 10:00 - 12:00
Do, 12.02.2026 10:00 - 12:00
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