Module MA2510-KP04, MA2510

Stochastics 1 (Stoch1)


Duration

1 Semester

Turnus of offer

each summer semester

Credit points

4

Course of studies, specific fields and terms:

  • Minor in Teaching Mathematics, Bachelor of Arts 2023, compulsory, mathematics
  • Bachelor CLS 2023, compulsory, mathematics
  • Bachelor MES 2020, optional subject, mathematics / natural sciences
  • Bachelor Computer Science 2019, compulsory, mathematics
  • Bachelor Robotics and Autonomous Systems 2020 , compulsory, mathematics
  • Bachelor Medical Informatics 2019, optional subject, mathematics
  • Minor in Teaching Mathematics, Bachelor of Arts 2017, compulsory, mathematics
  • Bachelor Computer Science 2016, compulsory, mathematics
  • Bachelor CLS 2016, compulsory, mathematics
  • Bachelor Robotics and Autonomous Systems 2016, compulsory, mathematics
  • Bachelor IT-Security 2016, compulsory, mathematics
  • Bachelor Biophysics 2016, optional subject, mathematics
  • Bachelor Medical Informatics 2014, optional subject, mathematics
  • Bachelor MES 2014, optional subject, mathematics / natural sciences
  • Bachelor Computer Science 2014, compulsory, mathematics
  • Bachelor Computer Science 2012, compulsory, mathematics
  • Bachelor MES 2011, compulsory, mathematics
  • Bachelor CLS 2010, compulsory, mathematics

Classes and lectures:

  • Stochastic 1 (exercise, 1 SWS)
  • Stochastics 1 (lecture, 2 SWS)

Workload:

  • 45 hours in-classroom work
  • 65 hours private studies and exercises
  • 10 hours exam preparation

Contents of teaching:

  • probability spaces
  • basics of combinatorics
  • conditional probability and stochastic independency
  • random variables
  • important discrete and continuous one-dimensional probability distributions
  • characteristics of distributions
  • law of large numbers, central limit theorem
  • modeling examples from the life sciences

Qualification-goals/Competencies:

  • Students are able to explain basic stochastic models formally correct and in the context of their application
  • They are able to formalize stochastic problems
  • They are able to identify basic combinatorial patterns and to use them for solving stochastic problems
  • They understand central statements of elementary stochastics

Grading through:

  • written exam

Literature:

  • N. Henze : Stochastik für Einsteiger Vieweg
  • U. Krengel : Einführung in die Wahrscheinlichkeitstheorie Vieweg

Language:

  • offered only in German

Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Successful completion of homework assignments during the semester

Module exam(s):
- MA2510-L1: Stochastics 1, written exam, 90 min, 100 % of module grade

Last Updated:

24.07.2023