After successful completion of the course, students are able to
- compute probabilities of combined events and conditional probabilities,
- use important distribution functions for solving simple problems,
- estimate parameters (mean value, variance) of a population and their confidence intervals based on empirically collected sample data,
- apply hypothesis testing in order to correctly test claims regarding a characteristic of a population,
- use simple analysis of variance and linear regression to systematically process measured data and to see order in seeming chaos.
Explanation of basic notions, derivation of the governing equations, treatment of examples, discussion of case studies
This course is graded via immanent examination. Two compulsory written tests (examples) as well as online-tests (theory) constitute the final grading.
Additional minimum requirement: Each of the two written test results must be a minimum of 25 % of the maximum test points in order to have an overall positive result! This rule also applies to the repetition test.
If the overall result of the two tests is negative (due to a missed or negative written test), that test with the smaller number of points can be repeated (repetition test) at the end of the term.
