Statistics and Data Analysis

Module Code
Module Coordinators
Matthias Gundlach
  • Matthias Gundlach
  • 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 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