HS (MA): Politikwissenschaftliche Methoden I - Grundlagen der Wissenschaftstheorie

Dozent/in:

Johannes Marx

Angaben:

Hauptseminar, 2 SWS, ECTS: 8

Termine:

Do, 8:00 - 10:00, F21/03.79

HS: Politikwissenschaftliche Methoden III: MA/SM Introduction to R [HS: Politikwissenschaftliche Methoden III: MA/SM Introduction to R]

Dozent/in:

Florian Weiler

Angaben:

Hauptseminar, 2 SWS, ECTS: 8

Termine:

Blockveranstaltung 29.3.2016-1.4.2016 Mo-Fr, Sa, So, 9:00 - 18:00, RZ/01.02
Zeit nach Vereinbarung Blockveranstaltung 29.03.-01.04.2016

Voraussetzungen / Organisatorisches:

Master course: Hauptseminar - Politikwissenschaftliche Methoden III Time and date: Monday, 29 March - 1 April, 9am-16:00pm Venue: Room RZ/01.02 Registration: MA-Students: FlexNow; BAGSS PhDs: Please register by sending a mail to Marc Scheibner (marc.scheibner@uni-bamberg.de). Requirements: MA or PhD student ECTS: 8

Inhalt:

This workshop introduces students to many of the most commonly used features of R, an open source program for statistical computation. R provides the user with a wide variety of pre-programmed modeling and graphing techniques. But R is also a powerful programming language and allows users to adjust existing functions to their needs, and to write their own functions. This workshop intends to introduce students first to the R language, R’s object oriented approach to statistical modeling, and the basics of writing functions, and second to the most commonly used pre-proprammed statistical techniques. The Introduction to R lectures in the morning will be accompanied by lab sessions in the afternoon to provide students with a hands-on experience of the techniques covered in class. The lab is structured to be relatively unguided, providing participants the opportunity to begin digging into the R computing environment at their own pace. During each lab session I will hand out exercises to be completed independently, or in collaboration with other students. I will be at hand to answer questions and help with the almost inevitable coding problems beginners of R are usually faced with. At the end of the course students should be able to work with R independently

Empfohlene Literatur:

Introductory Readings Zuur, Alain, Elena Ieno, and Erik Meesters (2009). A Beginner’s Guide to R. Springer. Dordrecht, Heidelberg, London, New York: Springer. Fox, John, and Sanford Weisberg (2011). An R Companion to Applied Regression. 2nd edition, Thousand Oaks: Sage Publications, Inc. Muenchen, Robert A., and Joseph M. Hilbe (2010). R for Stata Users. Dordrecht, Heidelberg, London, New York: Springer. King, Garry, Kosuke Imai, and Olivia Lau (2008). Zelig: Everyone’s Statistical Software. http://http://projects.iq.harvard.edu/zelig.

HS: Politikwissenschaftliche Methoden II: MA/SM Qualitative Methods of Social Inquiry [HS: Politikwissenschaftliche Methoden II: MA/SM Qualitative Methods of Social Inquiry]

Dozent/in:

Ariadna Ripoll Servent

Angaben:

Hauptseminar, 2 SWS, ECTS: 8

Termine:

Mo, 12:00 - 14:00, FG1/00.06

Voraussetzungen / Organisatorisches:

Date: Mondays, 12:00–14:00 Room: FG1/00.06 ECTS: 8 Lecturer: Prof. Dr. Ariadna Ripoll Servent Office hours: Wednesdays, 11:30–12:30
Eligibility Requirements:
The working language of this course is English. All coursework must be completed in English.
Regular attendance and knowledge of the required readings will be expected.
MA students:
To obtain a certificate, participants will have to submit a portfolio of three data reports on developing a research question, using one qualitative method to gather data and another to analyse qualitative data. Please note: The number of participants is limited. Student registration via FlexNow! is required.

Inhalt:

This seminar-based course offers a broad introduction to the field of qualitative methods from a comparative perspective and beyond. It aims to situate the use of qualitative methods in different research traditions with the aim to uncover their advantages and limitations. The course is divided in four parts: the first part investigates the meaning of qualitative methods and its links with particular ways to investigate and understand the social world; the second part concentrates on various methods to gather qualitative data; the third (and main part) looks at how primary and secondary qualitative data can be used and analysed. It discusses the importance of theory, causality and how they are linked to the way we interpret and present our data. The final part of the course deals with the assessment of qualitative data and methods – discussing the standards of validity, reliability and generalisability as well as broader questions of ethics in social science research