Every winter semester
7 Credit points
For information on the duration of the modul, refer to the courses of study in which the module is used.
Non-official translation of the module descriptions. Only the German version is legally binding.
Students understand basic stochastic concepts as well as the foundations of probability theory and statistics; they acquire competences in modelling and analysis of complex relations using probabilistic structures as the basis for applications in particular in statistics. Moreover application examples provide first insights into the application of statistical analyses and modelling using statistical software. Students work in tutorials to improve their skills in the foundations of mathematics, the usage of probability theory for handling data sets in the context of statistics in particular using statistical software. Moreover in the tutorials also presentation and communication skills are acquired. The final exam demonstrates the acquired knowledge in terms of statistical concepts and their relations in the application of statistical methods.
I. Foundations
II. Estimation
III. Uncertainty Quantification
IV. Hypothesis testing
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Module structure: 1 bPr 1
Portfolio of exercises, which are usually set weekly during the course, and final examination (usually 90 min) or oral final examination (usually 30 min). The exercises supplement and deepen the content of the lecture.
Participation in exercise groups (presentation of calculation exercises twice when asked. The organiser may replace some of the exercises by exercises in attendance).
Proof of a sufficient number of correctly solved exercises (usually 50% of the points achievable in the semester for solving the exercises).
The final examination relates to the content of the lecture and the tutorial and is used for assessment.
| Degree programme | Profile | Recommended start 3 | Duration | Mandatory option 4 |
|---|---|---|---|---|
| Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] | Variante 1 | 1. | one semester | Obligation |
| Data Science / Master of Science [FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024] | Variante 2 | 1. | one semester | Obligation |
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