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| Semester | Herbstsemester 2017 |
| Angebotsmuster | einmalig |
| Dozierende | Florian Weiler (florian.weiler@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. In the following part of the course we will discuss the basics of statistical modelling, i.e. what is a model, how does it relate to the data generating process, and which are the elements needed in each statistical model. After this short theoretical part, we will 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. Next, we will discuss maximum likelihood estimation and then apply this technique to binary and categorical dependent variables (logit, probit, count models, etc.). In all these parts of the course, we will discuss how to improve the basic models. The focus of the course is not in mathematics, but to give students an intuition of how the different modelling techniques actually work. In addition, the course will be very hands-on and application-oriented. Thus, 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 | - Wooldridge, Jeffrey M. (2002). Introductory Econometrics. A Modern Approach. Mason, OH: Cengate Learning. - Fox, John (2008). Applied Regression Analysis. Los Angeles, London: Sage. - Fox, John and Sanford Weisberg (2011).An R Companion to Applied Regression. Los Angeles, London: Sage. - Agresti, Alan and Barbara Finlay (2009): Statistical Methods for the Social Sciences. Upper Daddle River, NJ: Pearson Prentice Hall. |
| 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.) |
| Anmeldung zur Lehrveranstaltung | durch Belegen in MOnA |
| Unterrichtssprache | Deutsch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
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Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Modul Culture and Society (Master Studiengang: African Studies (Studienbeginn vor 01.08.2013)) Modul Fields: Knowledge Production and Transfer (Master Studiengang: African Studies) Modul Methoden der Gesellschaftswissenschaften (Masterstudium: European Global Studies) Modul Politische, Kulturelle und Historische Grundlagen der Europäischen Integration (Masterstudium: European Studies (Studienbeginn vor 01.02.2015)) Modul: Empirische Forschungsmethoden (Master Studienfach: Politikwissenschaft) Modul: Vorbereitung Masterarbeit Gesellschaftswissenschaften (Masterstudium: Sustainable Development) |
| Leistungsüberprüfung | Lehrveranst.-begleitend |
| Hinweise zur Leistungsüberprüfung | Term paper (50%), 3 problem sets (50%) |
| An-/Abmeldung zur Leistungsüberprüfung | Anmelden: Belegen; Abmelden: nicht erforderlich |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Wiederholtes Belegen | nicht wiederholbar |
| Zuständige Fakultät | Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch |
| Anbietende Organisationseinheit | Fachbereich Politikwissenschaft |