Stud.IP Uni Oldenburg
University of Oldenburg
15.06.2021 01:43:06
phy731 - Compulsory Optional Subject Theory (Course overview)
Institute of Physics 6 KP
Module components Semester courses Wintersemester 2020/2021 Examination
Lecture
  • No access 5.04.4207 - Processing and analysis of biomedical data Show lecturers
    • PD Dr. Thomas Brand
    • PD Dr. Stefan Uppenkamp, Dipl.-Phys.
    • Dr. Stephan Ewert, Dipl.-Phys.

    Monday: 08:00 - 10:00, weekly (from 19/10/20)
    Thursday: 08:00 - 10:00, weekly (from 22/10/20)
    Dates on Friday. 12.02.21 09:00 - 11:00

    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.

Exercises
  • No access 5.04.4207 - Processing and analysis of biomedical data Show lecturers
    • PD Dr. Thomas Brand
    • PD Dr. Stefan Uppenkamp, Dipl.-Phys.
    • Dr. Stephan Ewert, Dipl.-Phys.

    Monday: 08:00 - 10:00, weekly (from 19/10/20)
    Thursday: 08:00 - 10:00, weekly (from 22/10/20)
    Dates on Friday. 12.02.21 09:00 - 11:00

    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 Physik, Technik und Medizin oder entsprechender Abschluss
Module examination
M
Skills to be acquired in this module
Theoretische Voraussetzungen für numerische und analytische Modellierung komplexer Vorgänge in der Medizin, Biologie und Biophysik erlangen, um Forschungs-Methoden und -Gegenstände des Exzellenzcluster Hearing4all im Modellierungsbereich anwenden zu können. Spezielle Kompetenzen abhängig von der gewählten Veranstaltung