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MA/SM: Introduction to R (MA/SM Introduction to R)
- Dozent/in
- Dr. Florian Weiler
- Angaben
- Vorlesung
Zeit und Ort: Blockveranstaltung 16.3.2015 9:00 - 19.3.2015 18:00, RZ/01.03
- Voraussetzungen / Organisatorisches
- Time and date: Monday, 30 March - Thursday, 2 April, 9am-16:00pm
Venue: Room RZ/01.03
Registration: Please register by sending a mail to Marc Scheibner
(marc.scheibner@uni-bamberg.de).
Requirements: Doctoral students admitted to the Bamberg Graduate School of Social
Sciences (BAGSS); MA in Political Science or equivalent qualification for visiting students
- Inhalt
- Course Description:
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.
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 20
- Institution: Professur für Empirische Politikwissenschaft
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