312.192 (19W) Seminar in Statistics

Wintersemester 2019/20

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04.10.2019 23:59

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Überblick

Lehrende/r
LV-Titel englisch
Seminar in Statistics
LV-Art
Seminar (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
4.0
Anmeldungen
7 (15 max.)
Organisationseinheit
Unterrichtssprache
Englisch
mögliche Sprache/n der Leistungserbringung
Englisch
LV-Beginn

LV-Beschreibung

Intendierte Lernergebnisse

The student should be able to carefully read and explain details of a scientific paper.

Lehrmethodik

The students will get the task to develop a project by reading a scientific paper, working it out carefully, and presenting it in front of the class.

Inhalt/e

There will be topics mainly in Statistics (supervised by G. Spöck) and topics in Stochastic Processes (supervised by M. Szölgyenyi).


The overall topic will be Machine Learning in Statistics and Stochastic Processes.

Statistics topic: "Artificial General Intelligence its limits and the most important mathematical and statistical tools".

Stochastic Processes topic: "Machine learning for solving stochastic differential equations"

Erwartete Vorkenntnisse

Knowledge in stochastics and stochastic processes.

Literatur

Scientific papers.

Prüfungsinformationen

Prüfungsmethode/n

The projects will be distributed at the beginning of the semester.
Then the projects  will be carefully worked out.
For this, the students will read a scientific papers under guidance and they will work it out carefully. 
Then all projects will be presented in front of the other students.

Prüfungsinhalt/e

The own topic and the participation in the seminar.

Beurteilungskriterien/-maßstäbe

The marks are based on the development of the project and the end presentation. Attendance is mandatory.

Sign-out without grading is possible until October 31, 2019.

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Doktoratsprogramm Modeling-Analysis-Optimization of discrete, continuous and stochastic systems (SKZ: ---, Version: 16W.1)
    • Fach: Modeling-Analysis-Optimization of discrete, continuous and stochastic systems (Pflichtfach)
      • Modeling-Analysis - Optimization of discrete, continuous and stochastic systems ( 0.0h XX / 0.0 ECTS)
        • 312.192 Seminar in Statistics (2.0h SE / 4.0 ECTS)
  • Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
    • Fach: Applied Statistics (Wahlfach)
      • 5.10 Seminar in Statistics ( 2.0h SE / 4.0 ECTS)
        • 312.192 Seminar in Statistics (2.0h SE / 4.0 ECTS)
  • Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
    • Fach: Applied Mathematics (Wahlfach)
      • Lehrveranstaltungen aus den Vertiefungsfächern ( 0.0h XX / 12.0 ECTS)
        • 312.192 Seminar in Statistics (2.0h SE / 4.0 ECTS)
  • Masterstudium Technische Mathematik (SKZ: 401, Version: 13W.1)
    • Fach: Seminar und Praktikum (Pflichtfach)
      • Seminar ( 2.0h SE / 4.0 ECTS)
        • 312.192 Seminar in Statistics (2.0h SE / 4.0 ECTS)
  • Doktoratsstudium Doktoratsstudium der Technischen Wissenschaften (SKZ: 786, Version: 12W.4)
    • Fach: Studienleistungen gem. § 3 Abs. 2a des Curriculums (Pflichtfach)
      • Studienleistungen gem. § 3 Abs. 2a des Curriculums ( 16.0h XX / 32.0 ECTS)
        • 312.192 Seminar in Statistics (2.0h SE / 4.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2019
  • 312.192 SE Seminar in Statistics (2.0h / 4.0ECTS)
Wintersemester 2018/19
  • 312.192 SE Seminar in Statistics (Stochastic Processes) (2.0h / 4.0ECTS)
Sommersemester 2018
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)
Sommersemester 2017
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)
Sommersemester 2016
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)
Wintersemester 2015/16
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)
Wintersemester 2014/15
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)
Sommersemester 2014
  • 312.192 SE Seminar aus Statistik (2.0h / 4.0ECTS)