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48555-01 - Seminar: Research Methods in Social and Political Science 3 KP

Semester Herbstsemester 2022
Angebotsmuster Jedes Herbstsemester
Dozierende Daniel Höhmann (daniel.hoehmann@unibas.ch, BeurteilerIn)
Inhalt This course is designed for students interested in quantitative research methods and statistical analysis who already possess some basic knowledge about statistics and, if possible, regression analysis. In the first three weeks of the course, we revisit some of the fundamentals of statistical inference (such as the Central Limit Theorem, hypotheses tests, etc.) to offer students with limited statistical background the possibility the catch up with the required knowledge. Next, we cover the classical linear regression model, the assumptions we make when running such a model, and how violations of these assumptions can be detected and fixed. In the next section of the course we will discuss maximum likelihood estimation and then apply this technique to binary and categorical dependent variables (logit, probit, count models, etc.). The focus of the course is not in mathematics, but to give students an intuition of how the different modelling techniques actually work. At the end of the course participants should be able to apply the covered material to their own research. In addition, students should learn how to graphically present the results of the models for professional publications.
Lernziele - Learn the most important statistical estimation techniques for political scientists.
- Learn how to use model diagnostics to improve the model.
- Learn how to graphically represent the model to better convey the results to the audience during presentations or to readers in papers.
Literatur - Kellstedt, Paul & Guy Whitten (2013). The Fundamentals of Political Science Research. Cambridge: Cambridge University Press.
- Weelan, Charles (2013). Naked Statistics. Stripping the Dread from the Data. New York: W.W. Norton.
- Lewis‐Beck, Colin and Michael Lewis-Beck (2016). Applied Regression: An Introduction. London: Sage.
- Best, Henning & Christof Wolf (2015). The SAGE Handbook of Regression Analysis and Causal Inference. Sage: London.
Bemerkungen Attention:
Priority will be given to students of Political Science and Sociology. If there are more students than places in this first session, we will distribute the places according the date of registration to the course in Mona.
All Seminars will be graded in the Department of Political Science.
Grading scale 6.0 to 1.0, whereupon 4.0 is a pass.

 

Teilnahmebedingungen - Knowledge of introductory statistics. In the first three weeks of the course, we revisit some of the fundamentals of statistical inference (such as the Central Limit Theorem, hypotheses tests, etc.) to offer students with limited statistical background the possibility the catch up with the required knowledge.)

Priority will be given to students of Political Science and Sociology. If there are more students than places in this first session, we will distribute the places according the date of registration to the course in Mona.
Anmeldung zur Lehrveranstaltung durch Belegen in MOnA
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz

 

Intervall wöchentlich
Datum 22.09.2022 – 22.12.2022
Zeit Donnerstag, 14.15-15.45 Bernoullistrasse 14/16, Seminarraum 02.004
Datum Zeit Raum
Donnerstag 22.09.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 29.09.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 06.10.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 13.10.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 20.10.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 27.10.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 03.11.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 10.11.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 17.11.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 24.11.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 01.12.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 08.12.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 15.12.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Donnerstag 22.12.2022 14.15-15.45 Uhr Bernoullistrasse 14/16, Seminarraum 02.004
Module Modul: Empirische Forschungsmethoden der Politikwissenschaft und der Gesellschaftswissenschaften (Master Studienfach Politikwissenschaft)
Modul: Fields: Knowledge Production and Transfer (Master Studiengang African Studies)
Modul: Methoden der Gesellschaftswissenschaften (Masterstudium: European Global Studies)
Modul: Methoden der Near & Middle Eastern Studies und der Gesellschaftswissenschaften (Master Studienfach Near & Middle Eastern Studies)
Modul: Methoden der Soziologie und der Gesellschaftswissenschaften: quantitativ (Master Studienfach Soziologie)
Modul: Methods for Analyzing Changing Societies (Master Studiengang Changing Societies: Migration – Conflicts – Resources )
Modul: Research Skills (Master Studiengang African Studies)
Modul: Theorien und Methodologien der Kulturanthropologie (Master Studienfach Kulturanthropologie)
Modul: Vorbereitung Masterarbeit Gesellschaftswissenschaften (Masterstudium: Sustainable Development)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung To pass the seminar, students have to write a term paper that uses any publicly available data set to demonstrate their ability to conduct a data analysis.

All Seminars will be graded in the Department of Political Science.
Grading scale 6.0 to 1.0, whereupon 4.0 is a pass.
An-/Abmeldung zur Leistungsüberprüfung Anmelden: Belegen; Abmelden: nicht erforderlich
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,5
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch
Anbietende Organisationseinheit Fachbereich Politikwissenschaft

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