1. Solution of partial differential equations
2. Basics of data analysis
   
   1. Analysis of spatial data
   2. Time series analysis
3. Fourier transformation
4. Spectral theory and digital filters
5. Analysis methods of spatial data
6. Analysis methods of time series

• W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, “Numerical Recipies”, Cambridge University Press
• N. Köckler, „Numerische Algorithmen in Softwaresystemen“, Teubner, 1990

• J. Stoer, „Einführung in die Numerische Mathematik I“, Springer Verlag, 1983 (ggf. neuere Auflage)
• J. Stoer, R. Bulirsch, „Einführung in die Numerische Mathematik II“, Springer Verlag, 1978 (ggf. neuere Auflage)

This module is a non compensable obligatory module. It is passed if

1. lectures and tutorials were attended regularly and successfully (at least 50% of the in the tutorials accessible points have to be gained).
2. the test is passed. If the test is not passed there will be the opportunity for a timely re-test (written or oral). If the re-test is not passed it is recommended to retry the course of the module with a subsequent second re-test. If the re-test is not passed the module is failed.

• Extended knowledge of the basics of numeric
• Extended knowledge of the most important numerical algorithms
• Basic knowledge of numerical dealing with partial differential equations and terms: consistence, convergence, stability
• Basic knowledge in methods of data analysis, also under Bayesian aspects
• Ability to edit data sets due to applied filters

Passed modules:

1. Mathematik für Physiker I
2. Mathematik für Physiker II
3. Datenverarbeitung und Programmieren

• Extended knowledge of application and evaluation of numerical algorithms and of algorithms for data analysis