Technische Universität Ilmenau

Scientific Work and Empirical Research - Modultafeln of TU Ilmenau

The Modultafeln have a pure informational character. The legally binding information can be found in the corresponding Studienplan and Modulhandbuch, which are served on the pages of the course offers. Please also pay attention to this legal advice (german only). Information on place and time of the actual lectures is served in the Vorlesungsverzeichnis.

subject properties Scientific Work and Empirical Research in major Master Medien- und Kommunikationswissenschaft/Media and Communication Science 2013
subject number9188
examination number90102
departmentDepartment of Economic Sciences and Media
ID of group 2551 (Group for Media Research and Political Communication)
subject leaderProf. Dr. Jens Wolling
term ganzjährig
credit points3
on-campus program (h)34
self-study (h)56
examalternative examination performance
details of the certificate

Students write a research paper based on their own statistical analysis.

maximum number of participants
previous knowledge and experience

Basic knowledge in social science research methods and statistics (basic graduate level).

learning outcome
  • Students are able to understand and explain complex research designs.
  • Students are able to organize, prepare and modify empirical data for statistical analysis.
  • Students understand how to apply different methods of uni-, bi- and multivariate analysis of quantitative data to answer research questions.
  • Students interpret and explain the results of advanced statistical analyses.

In the seminar the principles and the statistical background of basic methods of data analysis are explained. These methods are applied to specific research problems. Therefore, real research data are analyzed using R.

Proceedings of data modification and index building are trained (Compute, Recode etc.) and different techniques of uni-, bi- and multivariate analysis of quantitative data are learned (Frequencies, Means, Crosstabs, Correlation Analysis, Regression Analysis, Analysis of Variance, Factor Analysis etc.).

media of instruction

Power Point Presentation, Empirical Data, Questionnaires

literature / references


  • Stinerock, R. (2018): Statistics with R – A Begniner’s Guide. New Delhi: Sage
  • Field, A. (2012): Discovering Statistics Using R. London, Thousand Oaks and New Delhi: Sage.
  • Fielding, J. (2007): Understanding Social Statistics (2nd ed.). Los Angeles et al.: Sage.
  • Teetor, P. (2011): R Cookbook – Proven Recipes for Data Analysis, Statistics, and Graphics. O’ Reilly: Boston.


Online Resources:

evaluation of teaching