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| Detailinformationen |
| Anmeldevoraussetzungen |
(*)keine
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| Quellcurriculum |
Masterstudium Statistics and Data Science 2025W |
| Lernergebnisse |
Kompetenzen |
| (*)Students are able to design their own experiment efficiently and judge other experiments accordingly.
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| Fertigkeiten |
Kenntnisse |
(*)- Knowing and understanding of the basic problems, concepts and procedures of experimental design (k1,k2)
- Constructing, applying and critically evaluating different sampling designs (k3,k4, k5)
- Using software to generate experimental designs R (k3)
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(*)- randomization, blocking, replication
- simple factorial designs, fractional factorials
- screening designs
- response surface designs
- optimal design of experiments
- design algorithms
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| Beurteilungskriterien |
(*)Presentation and written description of a concrete designed experiment, homework exercises, final exam
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| Lehrmethoden |
(*)Lecture and interactive work with experimental design software
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Atkinson A. C., Donev A. N. and Tobias R. D. (2007). Optimum Experimental Designs, with SAS. Oxford University Press.
Anderson M. J. and Whitcomb P. J. (2007). DOE Simplified: Practical Tools for Effective Experimentation, Second Edition, 2nd Edition. Productivity Press.
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| Lehrinhalte wechselnd? |
Nein |
| Gilt als absolviert, wenn |
(*)5MSVPKV: KV Versuchsplanung (6 ECTS)
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