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Statistics and Statistical Learning
(dt. Statistik und statistische Lernverfahren)

Level, degree of commitment Specialization module, depends on importing study program
Forms of teaching and learning,
workload		 Lecture (4 SWS), recitation class (2 SWS),
270 hours (90 h attendance, 180 h private study)
Credit points,
formal requirements		 9 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises.
Examination type: Oral examination (individual examination) or written examination
Language,
Grading		 English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Business Mathematics.
Origin M.Sc. Business Mathematics, M.Sc. Business Mathematics
Duration,
frequency		 One semester,
i.d.R. jedes Sommersemester
Person in charge of the module's outline Prof. Dr. Hajo Holzmann

Contents

Translation is missing, sorry. German original:

  • Grundlagen der Statistik: Statistische Modelle, Schätzen, Testen, Konfidenzintervalle
  • Statistik im linearen Modell, die multivariate Normalverteilung
  • Exponentialfamilien und verallgemeinerte lineare Modelle
  • Grundlagen des überwachten Lernens: Klassifikation und Regression
  • Elemente des nicht-überwachten Lernens: Clusteranalyse und Hauptkomponentenanalyse
  • Unverzerrtes Schätzen und die Cramer - Rao Schranke

Qualification Goals

Translation is missing, sorry. German original:

Die Studierenden

  • können wichtige Verfahren der Statistik und des statistischen Lernens erläutern und können diese mathematisch analysieren,
  • können die Verfahren auf Datensätze mit Hilfe der Statistik Software R anwenden,
  • verstehen Datenanalyse und Statistik.

Prerequisites

None. The competences taught in the following modules are recommended: Elementary Probability and Statistics, Internship Stochastics.


Applicability

The module can be attended at FB12 in study program(s)

  • B.Sc. Mathematics
  • B.Sc. Business Mathematics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Mathematics

When studying M.Sc. Business Mathematics, this module can be attended in the study area Compulsory Elective Modules in Mathematics.

The module can also be used in other study programs (export module).


Recommended Reading

  • Hastie, T., Tibshirani, R., Friedman, J. (2011). The Elements of Statistical Learning. Springer.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2025/26. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

  • Winter 2016/17 (no corresponding element)
  • Summer 2018 (no corresponding element)
  • Winter 2018/19 (no corresponding element)
  • Winter 2019/20 (no corresponding element)
  • Winter 2020/21 (no corresponding element)
  • Summer 2021 (no corresponding element)
  • Winter 2021/22 (no corresponding element)
  • Winter 2022/23 (no corresponding element)
  • Winter 2023/24 (no corresponding element)
  • Winter 2025/26

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.