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Forecasting: Theory and Practice
(dt. Vorhersagen in Theorie und Praxis)

Level, degree of commitment Specialization module, compulsory elective module
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: Written or oral examination (individual 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.
Duration,
frequency		 One semester,
i.d.R. jedes zweite Wintersemester
Person in charge of the module's outline Prof. Dr. Sebastian Lerch

Contents

Translation is missing, sorry. German original:

  • Punkt- und probabilistische Vorhersagen zur Datenanalyse in verschiedenen Anwendungsbereichen
  • Kalibration und Schärfe von Vorhersagen
  • Mathematische Methoden zur Bewertung von Vorhersagen
  • Statistische Tests zur Vorhersagegenauigkeit von Prognosemethoden
  • Kombination von Verteilungsvorhersagen
  • Methoden zur Erstellung probabilistischer Vorhersagen aus Statistik und maschinellem Lernen

Qualification Goals

Translation is missing, sorry. German original:

Die Studierenden

  • kennen wichtige Verfahren der Statistik und des maschinellen Lernens zur Erstellung von Vorhersagen sowie mathematische Methoden zu deren Bewertung 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: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis, Elementary Probability and Statistics, Internship Stochastics, Statistics and Statistical Learning.


Applicability

Module imported from M.Sc. Business Mathematics.

It 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. Computer Science, this module can be attended in the study area Profile Area Mathematics.


Recommended Reading

  • Will be announced in the course.



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.