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

Distribution functions (part 2), multidimensional random structures, design of experiments, significance tests of hypotheses and their applications, investigation of measured data, time-dependent statistics, possibility and limits of model building and simulation, random number generation; the lecture conveys the theoretical basics and in the exercise the lecture contents are implemented by programming tasks based on practical examples.

Students will be able to model and examine technical systems in their conception phase using sophisticated methods and thus efficiently contribute to research and development. They are able to transfer and apply the acquired knowledge in new contexts. They can critically question learned methods and thus decide whether they are suitable for given problems. Through the acquired mathematical understanding, they can modify learned tools for new problems in a suitable manner.

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