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

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

Institut für Physik 6 KP
Modulteile Semesterveranstaltungen Wintersemester 2019/2020 Prüfungsleistung
Vorlesung
Übung
  • Kein Zugang 5.04.4207 - Processing and analysis of biomedical data Lehrende anzeigen
    • Thomas Brand
    • Dr. Stefan Uppenkamp, Dipl.-Phys.
    • Dr. Stephan Ewert, Dipl.-Phys.

    Montag: 08:00 - 10:00, wöchentlich (ab 14.10.2019), Ort: W16A 004
    Donnerstag: 08:00 - 10:00, wöchentlich (ab 17.10.2019), Ort: W01 0-008 (Rechnerraum)
    Termine am Donnerstag, 13.02.2020 08:30 - 10:30, Ort: W16A 004

    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
Teilnahmevoraussetzungen
Bachelor in Hörtechnik und Audiologie oder entsprechend
Hinweise
Vorlesung: 2 SWS, Übungen: 2 SWS
Prüfungsleistung Modul
eine Klausur
Kompetenzziele
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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