phy820 - Theorie II (Processing and Analysis of Biomedical Data)

phy820 - Theorie II (Processing and Analysis of Biomedical Data)

Institute of Physics 6 KP
Module components Semester courses Wintersemester 2022/2023 Examination
Lecture
Exercises
  • No access 5.04.4207 - Processing and analysis of biomedical data Show lecturers
    • Thomas Brand
    • Dr. Stefan Uppenkamp, Dipl.-Phys.
    • Dr. Stephan Ewert, Dipl.-Phys.

    Monday: 08:15 - 09:45, weekly (from 17/10/22), Location: W03 2-240
    Thursday: 08:15 - 09:45, weekly (from 20/10/22), Location: W01 0-008 (Rechnerraum)
    Dates on Monday, 20.02.2023 08:00 - 10:00, Location: W01 0-015
    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.
Hinweise zum Modul
Prerequisites
Bachelor in Hörtechnik und Audiologie oder entsprechend
Reference text
Vorlesung: 2 SWS, Übungen: 2 SWS
Module examination
KL
Skills to be acquired in this module
This course introduces basic concepts of statistics and signal processing and applies them to real world examples of biomedical 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 data sets in a meaningful manner.

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