Duration:
1 Semester | Turnus of offer:
each winter semester | Credit points:
7 |
Course of studies, specific field and terms: - Bachelor CLS 2023 (compulsory), mathematics, 3rd semester
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Classes and lectures: - Stochastics 2 (exercise, 2 SWS)
- Stochastics 2 (lecture, 3 SWS)
| Workload: - 20 Hours exam preparation
- 75 Hours in-classroom work
- 115 Hours private studies and exercises
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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
- characteristic functions
- conditional expectations
- basis ideas of information theory
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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 acquire a basic understanding of information theory approaches
- They are able to formalize complex stochastic problems
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Grading through: |
Requires: |
Responsible for this module: Teachers: |
Literature: - J. Elstrodt: Maß- und Integrationstheorie - Springer
- M. Fisz: Wahrscheinlichkeitsrechnung und mathematische Statistik - Deutscher Verlag der Wissenschaften
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Language: |
Notes:Admission requirememnts for taking the module: - None (The competencies of the modules listed under 'Requires' are needed for this module, but are not a formal prerequisite) Admission requirements for participation in module examination(s): - Successful completion of homework assignments during the semester Module exam(s): - MA4020-L1: Stochastics 2, written exam, 90 min, 100 % of module grade The lecture is identical to the one in module MA4020. |
Letzte Änderung: 22.2.2022 |
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