312.180 (19S) Stochastic Processes
Überblick
- Lehrende/r
- LV-Titel englisch Stochastic Processes
- LV-Art Vorlesung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 5
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 07.03.2019
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
The students should be able to define a stochastic process.
The students should be able to work with Markov chains.
The students should know branching processes.
The students should understand martingales.
The students should know Brownian motion and properties thereof.
The students should know Poisson processes and compound Poisson processes.
Lehrmethodik inkl. Einsatz von eLearning-Tools
Lecture with practical examples
Combination of slides and blackboard
Inhalt/e
Examples and Definitions
Markov chains
Martingales
Brownian motion
Poisson process
Compound Poisson process
Erwartete Vorkenntnisse
Stochastics 2
Prüfungsinformationen
Prüfungsmethode/n
There will be a final exam, presumably at the end of June.
The point scheme is as follows:
100-87 p. -> 1
86-75 p. -> 2
74-62 p. -> 3
61-50 p. -> 4
49-0 p. -> 5
Prüfungsinhalt/e
Everything that is covered in the lecture.
If additional reading is required for the lecture, this will be clearly announced in the lecture.
Beurteilungskriterien/-maßstäbe
The mark depends only on the number of points the student achieves at the final exam.
Beurteilungsschema
Note BenotungsschemaPosition 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)
- 312.180 Stochastic Processes (2.0h VO / 3.0 ECTS)
-
Modeling-Analysis - Optimization of discrete, continuous and stochastic systems (
0.0h XX / 0.0 ECTS)
-
Fach: Modeling-Analysis-Optimization of discrete, continuous and stochastic systems
(Pflichtfach)
- Masterstudium Mathematics
(SKZ: 401, Version: 18W.1)
-
Fach: Statistics
(Pflichtfach)
-
3.2 Stochastic Processes (
2.0h VO / 3.0 ECTS)
- 312.180 Stochastic Processes (2.0h VO / 3.0 ECTS)
-
3.2 Stochastic Processes (
2.0h VO / 3.0 ECTS)
-
Fach: Statistics
(Pflichtfach)
- Masterstudium Technische Mathematik
(SKZ: 401, Version: 13W.1)
-
Fach: Statistik
(Pflichtfach)
-
Stochastische Prozesse 1 (
3.0h VU / 5.0 ECTS)
- 312.180 Stochastic Processes (2.0h VO / 3.0 ECTS)
-
Stochastische Prozesse 1 (
3.0h VU / 5.0 ECTS)
-
Fach: Statistik
(Pflichtfach)
- 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)
- 312.180 Stochastic Processes (2.0h VO / 3.0 ECTS)
-
Studienleistungen gem. § 3 Abs. 2a des Curriculums (
16.0h XX / 32.0 ECTS)
-
Fach: Studienleistungen gem. § 3 Abs. 2a des Curriculums
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Sommersemester 2024
- 312.180 VO Stochastic Processes (2.0h / 3.0ECTS)
-
Sommersemester 2023
- 312.180 VO Stochastic Processes (2.0h / 3.0ECTS)
-
Sommersemester 2022
- 312.180 VO Stochastic Processes (2.0h / 3.0ECTS)
-
Sommersemester 2021
- 312.180 VO Stochastic Processes (2.0h / 3.0ECTS)
-
Sommersemester 2020
- 312.180 VO Stochastic Processes (2.0h / 3.0ECTS)