312.181 (19S) Stochastic Processes, exercises
Überblick
- Lehrende/r
- LV-Titel englisch Stochastic Processes, exercises
- LV-Art Übung (prüfungsimmanente LV )
- Semesterstunde/n 1.0
- ECTS-Anrechnungspunkte 2.0
- Anmeldungen 2 (25 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 14.03.2019
- eLearning zum Moodle-Kurs
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
Mandatory Exercises
Presentation of solution to exercises on the blackboard by the students
Inhalt/e
Examples and Definitions
Markov chains
Martingales
Brownian motion
Poisson process
Compound Poisson process
Erwartete Vorkenntnisse
Stochastics 2
Prüfungsinformationen
Prüfungsmethode/n
There are 100 p. in total. The number of exercises solved counts 80 p., the presentation in total counts 20 p.
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 Stochastic Processes.
Beurteilungskriterien/-maßstäbe
The mark depends only on the number of points the student achieves.
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)
- 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 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 (
1.0h UE / 2.0 ECTS)
- 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 ECTS)
-
3.2 Stochastic Processes (
1.0h UE / 2.0 ECTS)
-
Fach: Statistics
(Pflichtfach)
- Masterstudium Technische Mathematik
(SKZ: 401, Version: 13W.1)
-
Fach: Statistik
(Pflichtfach)
-
Stochastische Prozesse 1 (
3.0h VU / 5.0 ECTS)
- 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 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)
- 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 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
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2023
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2022
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2021
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2020
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)