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Module guide

Module MA4020 T

Module part: Stochastics 2 (Stoch2a)

Duration:


1 Semester
Turnus of offer:


each winter semester
Credit points:


4
Course of studies, specific field and terms:
  • Master Computer Science 2019 (module part), module part, arbitrary semester
  • Master Computer Science 2014 (module part), module part, arbitrary semester
Classes and lectures:
  • Stochastics 2 (exercise, 1 SWS)
  • Stochastics 2 (lecture, 2 SWS)
Workload:
  • 45 Hours in-classroom work
  • 65 Hours private studies and exercises
  • 10 Hours exam preparation
Contents of teaching:
  • Lebesgue integral and Riemann integral
  • Transformations of measures and integrals
  • Product measures and Fubini's theorem
  • Moments and dependency measures
  • Normally distributed random vectors and distributions closely related to the normal distribution
Qualification-goals/Competencies:
  • Studends get insights into basic stochastic structures
  • They master techniques of integration being relevant to stochastics
  • They master the treatment of (particularly normally distributed) random vectors and their distributions
  • They are able to formalize complex stochastic problems
Grading through:
  • exam type depends on main module
  • Exercises
Is requisite for:
Requires:
Responsible for this module:
  • Siehe Hauptmodul
Teachers:
Literature:
  • J. Elstrodt: Maß- und Integrationstheorie - Springer
  • M. Fisz: Wahrscheinlichkeitsrechnung und mathematische Statistik - Deutscher Verlag der Wissenschaften
Language:
  • offered only in German
Notes:

The lecture is identical to that in module MA4020-MML.

Prerequisites for attending the module:
- None

Prerequisites for the exam:
- Successful completion of homework assignments during the semester.

Letzte Änderung:
18.8.2020