Exam, exercise performance can flow into the exam as bonus points

Statistical basics (part 1), introduction to simulation techniques, distribution functions (part 1), sample preparation, statistical basics (part 2), statistical evaluation of simulations, stochastic processes, discrete-time Markov chains, continuous-time Markov chains; the lecture contents are put into practice during the exercise, in particular a simple simulator is built in several consecutive exercises. The focus is on the modeling of problems from different contexts by means of suitable distribution functions as well as by Markov chains, and on the associated mathematical foundations.

The students can model and examine technical systems in their conception phase with sophisticated methods and thus efficiently participate in research and development. They have in-depth, practical knowledge of discrete-time simulation and can systematically set up and evaluate experiments. They can use discrete-time and continuous-time Markov chains for the modelling and investigation of technical systems and predict their performance with the help of queueing theory. They are able to transfer and apply the acquired knowledge in new contexts.

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