MathMods :: Joint MSc

Additional Info

• ECTS credits: 6
• Code: DT0654
• University: Hamburg University of Technology
• Semester: 2
• Lecturer 1: Matthias Schulte
• Objectives:

   

  This course provides an introduction to probability theory and stochastic processes with special emphasis on applications and examples. The first part covers some important concepts from measure theory, stochastic convergence and conditional expectation, while the second part deals with some important classes of stochastic processes.

• Topics:

   

  • Measure and probability spaces
  • Integration and expectation
  • Types of stochastic convergence
  • Law of large numbers
  • Central limit theorem
  • Radon-Nikodym theorem
  • Conditional expectation
  • Martingales
  • Markov chains
  • Poisson processes
• Prerequisites:

   

  Familiarity with the basic concepts of probability

• Books:
   
  • H. Bauer, Probability theory and elements of measure theory, second edition, Academic Press, 1981.
  • A. Klenke, Probability Theory: A Comprehensive Course, second edition, Springer, 2014.
  • G. F. Lawler, Introduction to Stochastic Processes, second edition, Chapman & Hall/CRC, 2006.
  • A. N. Shiryaev, Probability, second edition, Springer, 1996.