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Design of experiment. [ LSTAT2320 ]


5.0 crédits ECTS  22.5 h + 7.5 h   2q 

Teacher(s) Govaerts Bernadette ; Bogaert Patrick ;
Language French
Place
of the course
Louvain-la-Neuve
Main themes - Experimental cycle and strategies - Linear regression as a tool to analyse the results of a designed experiment - Problem formalisation and qualities of an experimental design - Factorial designs and derivatives - Designs for the estimation of response surfaces - Optimal designs - Experimental design as viewed by Taguchi - Designs for mixture experiments - Simultaneous optimisation of several responses - Simplex and EVOP methodology to optimise one response
Aims At the end of the course, the student will be awared of the interest of using a methodology to design experiments that provides a maximum information at the lower cost. He will gain knowledge on different possible classes of experimental designs and on the statistical methods available to analyse experiment results.

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.

Content The themes discussed in this course are : - Experimental cycle and strategies - Linear regression as a tool to analyse the results of a designed experiment - Problem formalisation and qualities of an experimental design - Factorial designs and derivatives - Designs for the estimation of response surfaces - Optimal designs - Experimental design as viewed by Taguchi - Designs for mixture experiments - Simultaneous optimisation of several responses - Simplex and EVOP methodology to optimise one response Each course subject is presented on a case study.
Other information Prerequistes Basis courses in statistics. Course in linear models. Evaluation: For all: written test on the course content and practical work. For those who follow the partim B: elaboration of a personal applied (in groups of 1 or 2) with oral discussion of work. Reference : Box G. et Draper N. et H. Smith [1987], Empirical Model-Building and Response Surfaces, Wiley, New York Khuri A. et Cornell J., [1987], Response surfaces : designs and analyses, Marcel Dekker. Myers R.H., Douglas C. Montgomery [1995], Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Wiley
Faculty or entity
in charge
> LSBA
Programmes / formations proposant cette unité d'enseignement (UE)
  Sigle Crédits Prérequis Acquis
d'apprentissage
Master [120] in Biomedical Engineering GBIO2M 5 -
STAT9CE 5 -
Master [120] in Statistics: Biostatistics BSTA2M 5 -
Master [120] in Statistics: General STAT2M 5 -
Master [120] in Computer Science and Engineering INFO2M 5 -
Master [120] in Computer Science SINF2M 5 -
Master [120] in Mathematical Engineering MAP2M 4 -
Master [120] in Agricultural Bioengineering BIRA2M 5 -
Master [120] in Chemistry and Bioindustries BIRC2M 5 -
Master [120] in Environmental Bioengineering BIRE2M 5 -
STAT2FC 5 -


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