Module MA4020 T

Duration

1 Semester

Turnus of offer

each winter semester

Credit points

4

Course of studies, specific fields and terms:

• Master Computer Science 2019, module part, Module part
• Master Computer Science 2014, module part, Module part

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:

• Modeling Biological Systems (MA4450)
• Stochastic processes and modeling (MA4610-KP04, MA4610)

Requires:

• Stochastics 1 (MA2510-KP04, MA2510)
• Linear Algebra and Discrete Structures 2 (MA1500-KP08, MA1500)
• Analysis 2 (MA2500-KP04, MA2500)

Responsible for this module:

• Siehe Hauptmodul

Teacher:

• Institute for Mathematics
• Nachfolge von Prof. Dr. rer. nat. Karsten Keller

Literature:

• J. Elstrodt : Maß- und Integrationstheorie Springer
• M. Fisz : Wahrscheinlichkeitsrechnung und mathematische Statistik Deutscher Verlag der Wissenschaften

Language:

• offered only in German

Notes:

Last Updated:

18.08.2020