Students understand the concept of probability; they understand the concept of random variables; they master simple discrete and continuous random distributions; they understand the transition from probability theory to statistics; they can estimate first simple characteristics of populations and, in particular, statistically confirm or refute first simple hypotheses about such characteristics.

Discrete mathematics

The course includes the following main topics:

• Probability and probability space (event space, concept of probability),
• Laplace space and elementary counting problems (combinatorics),
• Random variables and their distribution (random variable, discrete distributions using the binomial distribution, continuous distributions using the normal distribution),
• Transition from probability theory to statistics (population, characteristic and sample, first simple estimators, a first hypothesis test).

The following basic literature will be used in the course:

• Teschl, G., Teschl, S., Mathematics for Computer Scientists, Vol. 2, Springer, 2006;
• Schubert, M., Mathematics for Computer Scientists, Springer, 2012;
• Stingl, P., Mathematik für Fachhochshulen, Hanser, 1999;

Lecture, exercises, accompanying use of computer algebra systems (MATLAB) and digital media for self-study.

Final grade comprised of

• Class participation,
• Partial or final examination