This course introduces fundamental concepts and methods of probability and statistics with a focus on applications in computer science. Students will learn how to collect, describe, and analyze data, as well as how to make inferences and decisions under uncertainty. Topics include descriptive statistics, probability theory, random variables and distributions, estimation, hypothesis testing and regression analysis. Emphasis is placed on computational approaches, simulation techniques, and practical implementation using the R programming language. By the end of the course, students will be equipped with the statistical reasoning and analytical skills necessary to support data-driven problem solving in computer science.
- Dozent/in: Cyriax Brast
- Dozent/in: Egbert Falkenberg
- Dozent/in: Stefan Dusan Kresovic
- Dozent/in: Martin Simon
- Dozent/in: Hendrik Weichel