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| PHYS0931-1 | Data processing
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| Duration : | 15h Th, 30h Pr |
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| Number of credits : |
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| Lecturer : | Pierre Magain |
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Language(s) of instruction :
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| French language |
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Course contents :
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| 1. Introduction
- experimental errors and noise
- instrumental profile
2. Fourier analysis
- sampling and interpolation
- correlation
- spectral analysis
3. Modelling of data:
- inductive methods
- maximum likelihood
- least squares fitting
4. deconvolution
- Fourier methods
- direct elementary methods
- maximum entrop method
- bayesian methods
- MCS method |
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Learning outcomes of the course :
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| To understand and experiment the basic principles of experimental data processing in physical science. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Basics of algebra, mathematical analysis, probability and statistics. Introductory phyics. |
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Planned learning activities and teaching methods :
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| Computer exercises. The student will have to cope with typical examples of data, similar to those an experimental physicist may have to deal with in his research. |
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Mode of delivery (face-to-face ; distance-learning) :
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| Theoretical lectures (about 1h30).
Computer exercises (about 3h). |
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Recommended or required readings :
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| Photocopies of slides. |
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Assessment methods and criteria :
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| The examination consists in solving two data analysis problems, similar to those carried out during the computer exercises. This is followed by a discussion of the results and of the relevant methods. It may be completed by a theoretical question on the last part of the course, dealing with deconvolution. |
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Contacts :
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| Pierre Magain
Institut d'astrophysique et de Géophysique, Bat. B5c, allée du 6 Aout, 4000 Liège 1
(Sart Tilman).
Tél.: 04/366.97.53
E-mail : Pierre.Magain@ulg.ac.be |
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| Items online : |
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| Syllabus d'exercices |
| Explication des exercices réalisés lors des séances |
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