312.181 (24S) Stochastic Processes, exercises

Sommersemester 2024

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Erster Termin der LV
21.03.2024 17:30 - 18:15 N.2.01 On Campus
Nächster Termin:
02.05.2024 14:00 - 15:30 N.2.01 On Campus
Nächster gültiger Termin:
02.05.2024 17:30 - 18:15 N.0.43 On Campus

Überblick

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 11 (25 max.)
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 21.03.2024
eLearning zum Moodle-Kurs

Zeit und Ort

Liste der Termine wird geladen...

LV-Beschreibung

Intendierte Lernergebnisse

The students should know Markov chains.

The students should be able to define a stochastic process.

The students should understand martingales.

The students should know Brownian motion and properties thereof.

The students should know Poisson processes, compound Poisson processes, and Lévy processes.

The students should be able to simulate paths of certain stochastic processes.

Lehrmethodik

Mandatory exercises

The students should tick the solved exercises  and upload the solutions to Moodle before 12:00 midday on the day of the exercise class.

In the exercise class, the students present the solutions to the exercises.



Inhalt/e

Markov chains
Definitions
Martingales
Brownian motion
Poisson process
Compound Poisson process
Lévy processes
Simulation of stochastic processes

Erwartete Vorkenntnisse

Stochastics 2

Literatur

Lecture notes available

Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Prüfungsmethode/n

There are 100 P. in total. The number of exercises solved counts 80 P., the presentations count 20 P.

The point scheme is as follows:
[100 , 87.5] P. -> 1
(87.5 , 75] P. -> 2
(75 , 62.5] P. -> 3
(62.5 , 50] P. -> 4
(50 , 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 achieved.

Cancellation of participation without grading is possible until 31.03.2024.

Beurteilungsschema

Note 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)
        • 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 ECTS)
  • 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)
  • Masterstudium Mathematics (SKZ: 401, Version: 22W.1)
    • Fach: Statistics and Probability (Pflichtfach)
      • 3.2 Stochastic Processes ( 1.0h UE / 2.0 ECTS)
        • 312.181 Stochastic Processes, exercises (1.0h UE / 2.0 ECTS)
          Absolvierung im 2. Semester empfohlen

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

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)
Sommersemester 2019
  • 312.181 UE Stochastic Processes, exercises (1.0h / 2.0ECTS)