| Lecturer (assistant) | |
|---|---|
| Number | MGT001438V |
| Term | Wintersemester 2025/26 |
| Language of instruction | English |
| Position within curricula | See TUMonline |
- 23.02.2026 09:00-17:00 Externer Ort (siehe Anmerkung)
- 24.02.2026 09:00-17:00 Externer Ort (siehe Anmerkung)
- 25.02.2026 09:00-17:00 Externer Ort (siehe Anmerkung)
- 26.02.2026 09:00-17:00 Externer Ort (siehe Anmerkung)
- 27.02.2026 09:00-17:00 Externer Ort (siehe Anmerkung)
Objectives
At the end of the course, students can
- solve practical problems by selecting adequate, advanced statistical methods,
- apply statistical methods in a suitable analysis software, and
- present the obtained results in written form, also using advanced visualization methods for statistical data
- solve practical problems by selecting adequate, advanced statistical methods,
- apply statistical methods in a suitable analysis software, and
- present the obtained results in written form, also using advanced visualization methods for statistical data
Description
The diversity of data types in real-life scenarios leads to a manifold of statistical methods one must master. In this course, the students will learn about advanced statistical techniques (e.g., nonlinear and logistic regression, regularized regression, and time series analysis) for different research questions. The course consists of a practical part, including exercises in the statistical programming language R (visualization techniques, applying statistical methods to real-life data), and a complementary lecture about the statistical backgrounds of the selected methods. The main focus is on the practical aspects and the application in R.
Note that your own laptop is necessary for this course.
Note that your own laptop is necessary for this course.
Teaching and learning methods
The course is organized as a block of one week during the semester break (23.-27.02., 9AM-5PM, wth a one hour break).
Morning sessions will be mainly introductory presentations by the teacher. Most of the afternoon sessions will be free to work on the exercises for the final report with support from the teacher.
Note that your laptop is necessary for this course.
Morning sessions will be mainly introductory presentations by the teacher. Most of the afternoon sessions will be free to work on the exercises for the final report with support from the teacher.
Note that your laptop is necessary for this course.