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Module guide

Modul MA4020-KP05

Stochastics 2 (Stoch2KP05)

Duration:


1 Semester
Turnus of offer:


each winter semester
Credit points:


5
Course of studies, specific field and terms:
  • Minor in Teaching Mathematics, Master of Education 2023 (compulsory), mathematics, 1st semester
  • Bachelor Computer Science 2019 (optional subject), Extended optional subjects, Arbitrary semester
  • Bachelor IT-Security 2016 (optional subject), mathematics, Arbitrary semester
  • Minor in Teaching Mathematics, Master of Education 2017 (compulsory), mathematics, 1st semester
  • Bachelor Computer Science 2016 (optional subject), advanced curriculum, Arbitrary semester
  • Bachelor CLS 2016 (compulsory), mathematics, 3rd semester
Classes and lectures:
  • Stochastics 2 (exercise, 2 SWS)
  • Stochastics 2 (lecture, 2 SWS)
Workload:
  • 60 Hours in-classroom work
  • 70 Hours private studies and exercises
  • 20 Hours exam preparation
Contents of teaching:
  • Lebesgue integral und 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:
  • Exercises
  • written exam
Requires:
Responsible for this module:
Teachers:
Literature:
  • J. Elstrodt: Maß- und Integrationstheorie - Springer
  • M. Fisz: Wahrscheinlichkeitsrechnung und mathematische Statistik - Deutscher Verlag der Wissenschaften
Language:
  • offered only in German
Notes:

Admission requirements for taking the module:
- None (the competencies of the modules listed under

Letzte Änderung:
1.2.2022