Design of experiment.
[STAT2320]
[22.5h + 7.5h] 5 credits
This course is taught in the 2d semester.
Teacher(s): Patrick Bogaert, Bernadette Govaerts
Language: French
Level: Second
Aims
Main themes
- 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
Content and teaching methods
- 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 (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)
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