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Vorlesungsverzeichnis >> Fakultät Sozial- und Wirtschaftswissenschaften >>
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Introduction to R [Import]- Verantwortliche/Verantwortlicher
- Prof. Dr. Ulrich Schroeders
- Angaben
- Seminar
2 SWS, - Master-Students: Please register via FlexNow - BAGSS/Doctoral Students: Please send a mail to Miriam Schneider (miriam.schneider@uni-bamberg.de) to register.
- Voraussetzungen / Organisatorisches
- • Master-Students: Please register via FlexNow
• BAGSS/Doctoral Students: Please send a mail to Miriam Schneider (miriam.schneider@uni-bamberg.de) to register.
- Inhalt
- This seminar deals with introductory and intermediate aspects of R, an open source statistical program that has become in recent years more and more popular in the behavioral and social sciences. In principle, the R ecosystem provides the user with a huge variety of pre-programmed modeling techniques and visualization tools, but the flexibility and versatility comes at the cost of learning an often unintuitive programming language. In this seminar students are first introduced to the basic units of R (operators, objects, functions, etc.) and structures (if-else, ifelse, while, etc.). Thereafter, the entire process of data analysis is discussed in detail including a) reading in data, b) data preparation and handling, c) descriptive statistics, d) advanced statistical analyses, e) data visualization, and f) saving output. A focus of this seminar is on developing hands-on programming skills by solving real-world analytical problems, for example, how to assess large-scale data via Internet, effectively recode data or find a catchy visualization of results. Since R is taught from scratch, neither experience in R (or another programming language) nor usage of a specific software is necessary. However, prospective participants should possess a solid knowledge of basic statistical concepts (e.g., variance, covariance, correlation) and analytical techniques (e.g., regression analysis). To obtain full ECTS points, participants have to complete assignments every two weeks.
- Empfohlene Literatur
- ‒ Field, A., & Miles, J. (2012). Discovering Statistics Using R. London ; Thousand Oaks, Calif: Sage Publications Ltd.
‒ Kabacoff, R. (2015). R in Action: Data Analysis and Graphics with R. Shelter Island: Manning.
‒ Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. San Francisco: No Starch Press.
- Englischsprachige Informationen:
- Credits: 8
- Institution: Professur für Empirische Politikwissenschaft
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