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29.09.2022 23:47:39
phy820 - Theory II (Statistics) (Complete module description)
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Module label Theory II (Statistics)
Modulkürzel phy820
Credit points 6.0 KP
Workload 180 h
Präsenzzeit: 56 Stunden Selbststudium: 124 Stunden
Institute directory Institute of Physics
Verwendbarkeit des Moduls
  • Master's Programme Hearing Technology and Audiology (Master) > Mastermodule
Zuständige Personen
Brand, Thomas (Prüfungsberechtigt)
Hohmann, Volker (Prüfungsberechtigt)
Lücke, Jörg (Prüfungsberechtigt)
Uppenkamp, Stefan (Module counselling)
Neher, Tobias (Module counselling)
Ewert, Stephan (Module counselling)
Bachelor in Hörtechnik und Audiologie oder entsprechend
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.
Module contents
Normal distributions and significance testing, Monte-Carlo boot strap techniques, Linear regression, Correlation, Signal-to-noise estimation, Principal component analysis, Confidence intervals, Dipole source analysis, Analysis of variance. Each technique is explained, tested and discussed in the exercises
- Kirkwood B.R. and Sterne A.C., Essential Medical Statistics: 2nd editition. Blackwell Science. Oxford, 2003 - Cho, Z.H. and Singh J. P. J. M.: Foundations of Medical Imaging. John Wiley, New York, 1993 - Kutz, J.N. Data-Driven Modeling and Scientific Computation: Methods for complex systems and Big Data. Oxford University Press, Oxford, 2013
Language of instruction English
Duration (semesters) 1 Semester
Module frequency Wintersemester
Module capacity unlimited
Reference text
Vorlesung: 2 SWS, Übungen: 2 SWS
Modullevel / module level MM (Mastermodul / Master module)
Modulart / typ of module Pflicht / Mandatory
Lehr-/Lernform / Teaching/Learning method
Vorkenntnisse / Previous knowledge
Examination Prüfungszeiten Type of examination
Final exam of module
Form of instruction Exercises
Frequency --
Workload Präsenzzeit 0 h