0000000236 13S 4SWS VO Probability Theory   Hilfe Logo

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Allgemeine Angaben
Probability Theory 
Summer semester 2013
Research Department Mathematics Centre
(Contact information)
Angaben zur Abhaltung
Based on measure and integration theory, in this course the fundamental concepts of probability theory are presented. Of central importance are the different types of convergence, the concept of stochastic independence, and conditional expectations. In addition, the course will deal with the Radon-Nikodym theorem, product spaces and the construction of stochastic processes. For sequences of independent random variables, laws of large numbers and the central limit theorem will be proved. As an important generalization of partial sums of independent random variables, martingales will be introduced and on this basis we will investigate stopping times and prove the martingale convergence theorem.
Measure and integration theory
class lecture
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Rick Durrett; Probability: Theory and Examples, Cambridge University Press, 2010
Allan Gut; Probability: A Graduate Course, Springer, 2009
Achim Klenke; Wahrscheinlichkeitstheorie, Springer, 2009
Additional information
additional information