Event
The dates and events shown here are dynamically displayed from Stud.IP.
Therefore, if you have any questions, please contact the person listed under the item Lehrende/DozentIn (Lecturers) directly.
Event
Semester:
Winter term
2024
5.04.4207 Processing and analysis of biomedical data -
Event date(s) | room
- Montag, 14.10.2024 8:00 - 10:00
- Donnerstag, 17.10.2024 8:00 - 10:00
- Montag, 21.10.2024 8:00 - 10:00
- Donnerstag, 24.10.2024 8:00 - 10:00
- Montag, 28.10.2024 8:00 - 10:00
- Montag, 4.11.2024 8:00 - 10:00
- Donnerstag, 7.11.2024 8:00 - 10:00
- Montag, 11.11.2024 8:00 - 10:00
- Donnerstag, 14.11.2024 8:00 - 10:00
- Montag, 18.11.2024 8:00 - 10:00
- Donnerstag, 21.11.2024 8:00 - 10:00
- Montag, 25.11.2024 8:00 - 10:00
- Donnerstag, 28.11.2024 8:00 - 10:00
- Montag, 2.12.2024 8:00 - 10:00
- Donnerstag, 5.12.2024 8:00 - 10:00
- Montag, 9.12.2024 8:00 - 10:00
- Donnerstag, 12.12.2024 8:00 - 10:00
- Montag, 16.12.2024 8:00 - 10:00
- Donnerstag, 19.12.2024 8:00 - 10:00
- Montag, 6.1.2025 8:00 - 10:00
- Donnerstag, 9.1.2025 8:00 - 10:00
- Montag, 13.1.2025 8:00 - 10:00
- Donnerstag, 16.1.2025 8:00 - 10:00
- Montag, 20.1.2025 8:00 - 10:00
- Donnerstag, 23.1.2025 8:00 - 10:00
- Montag, 27.1.2025 8:00 - 10:00
- Donnerstag, 30.1.2025 8:00 - 10:00
Description
This course introduces basic concepts of statistics and signal processing and applies them to real-world examples of bio-medical data. In the second part of the course, recorded datasets are noise-reduced, analyzed, and discussed in views of which statistical tests and analysis methods are appropriate for the underlying data. The course forms a bridge between theory and application and offers the students the means and tools to set up and analyze their future datasets in a meaningful manner.
content:
Normal distributions and significance testing, Monte-Carlo bootstrap techniques, Linear regression, Correlation, Signal-to-noise estimation, Principal component analysis, Confi-dence intervals, Dipole source analysis, Analysis of variance
Each technique is explained, tested and discussed in the exercises.
content:
Normal distributions and significance testing, Monte-Carlo bootstrap techniques, Linear regression, Correlation, Signal-to-noise estimation, Principal component analysis, Confi-dence intervals, Dipole source analysis, Analysis of variance
Each technique is explained, tested and discussed in the exercises.
Lecturers
Study fields
- olt707 - Additional module „Specific knowledge”
SWS
4
Art der Lehre
Ausschließlich Präsenz
Lehrsprache
deutsch