Statistics and Data Analysis

Short Name
Statistik u. Datenanalyse
Module Code
Module Coordinator
  • Prof. Dr. Matthias Gundlach
  • Prof. Dr. Matthias Gundlach
  • Prof. Dr. Frank Recker
Short Description

Course in descriptive and inductive statistics under inclusion of fundamentals of probability theory and using the software R

Learning Objectives

Students are aware of the problems with large data and are able of editing and presenting data, in particular using software. They know and understand the basic elements of descriptive statistics and probability theory. In particular they can calculate probabilities and are familiar with elementary distributions. They know the basic ideas of inductive statistics and are able to use them. In particular they are able to apply basic methods for estimations and tests, also using software, correctly and to evaluate their results.

  • Descriptive statistics
  • Basic ideas (measures, frequencies, indices, representation)
  • Regression
  • Fundamentals of probability theory
  • Basic concepts (probability, random variable, distribution, density)
  • Distributions
  • Inductive statistics
  • Estimation of parameters
  • Testing of Hypotheses
  • Analysis of variance
  • Regression analysis
  • Software R
Duration in Semester
Instruction Language
Total Effort
6.0 CrP; an estimated 180 hours, of which approximately 60 are spent in class.
Weekly School Hours
Method of Instruction

Vorlesung 2 SWS, Übung 2 SWS

Requirements for the awarding of Credit Points

Examination: Qualifying condition: Successful practical work using R Exam

  • L. Fahrmeir et al :Statistik. Springer Verlag.
  • S. Ross: Statistik für Ingenieure und Natur-wissenschaftler. Spektrum Akademischer Verlag
  • L.Sachs, J. Hedderich: Angewandte Statistik, Springer
  • D. Wollschläger: Grundlagen der Datenanalyse mit R, Springer
Prerequisite for Modules