University of Bamberg
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Faculty of Social Sciences, Economics, and Business Administration

  1.  University of bamberg
  2. Master Survey Statistics and Data Analysis
  3. Faculties
  4. Social Sciences, Economics and Business Administration
  5. Subjects and Institutes
  6. Institute for Statistics
  7. Departments & Professorships
  8. Chair of Statistics and Econometrics
  9. Teaching
  10. Prerequisites for Admission, Your Application & Introductory Course

Prerequisites for Admission and Your Application

 

Prerequisites of Admission  

 

  • Non-native speakers further have to provide proof of the language level B2 or higher. For further information click here.
  • The course of studies adresses students having concluded an university degree (or equivalent) in social siences, economics, mathematics, psychology or other disciplines relevant for statistics with grade 2.5 (good) or better.
  • Moreover knowledge of modules with statistical and or quantitative methodical orientation to the extent of at least 30 ECTS credits have to be proven. This knowledge could have been acquired in courses of descriptive, inductive, multivariate as well as computer-assisted statistics, mathematical propaedeutics and econometrics or subject-specific empirical research methods.
  • The overall grade of at least "good" as an admission requirement is waived if knowledge of statistics/ quantitative methods to the extent of 50 ECTS credits with an average grade of at least 2.5 can be demonstrated for the modules considered.
  • Foreign grades are converted using the Bavarian formula(86.2 KB).

Your Application

The programme can be taken up in the winter and summer semester. Applications can only be submitted online, usually by the closing date for enrollment of the respective semester. You can find information about the application and deadlines here.

If (suspected) deficiencies in statistical and/or quantitative-methodological knowledge exist (<30 ECTS credits), there are ways to make up for the missing knowledge relatively easily and with minimal time loss. This includes relevant foundational modules with a quantitative-methodological and/or statistical focus (e.g., as part of a preparatory module course before admission to the Master's program in Survey Statistics and Data Analysis) that can be completed to meet the admission requirements for the program.