312.181 (22S) Stochastic Processes, exercises
Überblick
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- Lehrende/r
- LV-Titel englisch Stochastic Processes, exercises
- LV-Art Übung (prüfungsimmanente LV )
- LV-Modell Präsenzlehrveranstaltung
- Semesterstunde/n 1.0
- ECTS-Anrechnungspunkte 2.0
- Anmeldungen 10 (25 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 03.03.2022
- 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
Mandatory exercises
The exercise class will take place every Thursday from 11am-12pm. The solutions to the exercises have to be submitted via Moodle until 8 am on the day of the exercise class. The solutions have to be presented by the students.
The students should tick the solved exercises until 8 am on the day of the exercise class. If we have to switch to the online class due to the pandemic, the students have to present the solved exercises online via BigBlueButton.
Inhalt/e
Examples and Definitions
Markov chains
Martingales
Brownian motion
Poisson process
Compound Poisson process
Erwartete Vorkenntnisse
Stochastics 2
Literatur
Lecture notes available
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.
Since the students will be graded during the course, students can cancel their registration without being graded until inclusively 31.03.2022.
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)
- 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
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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 2021
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2020
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)
-
Sommersemester 2019
- 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)