Modeling and design of experiments

Summary

In the academic or industrial world, to optimize a system, it is necessary to establish strategies for the experimental approach. The DOE allows you to choose the best set of measurement points to minimize the variance of the results. The concepts learned are applicable in all areas.

Content

Keywords

Design of experiments, ANOVA, Least square fit, Statistics, Multilineal regression, variance minimization

Learning Prerequisites

Recommended courses

Statistics, metrology

Important concepts to start the course

Basic statistical conceps such as average, variance, statistical distributions, Calculus, linear algebra matriciel, Matlab or Python fundamentals, coding fundamentals

Learning Outcomes

By the end of the course, the student must be able to:

• Propose an empirical model in function of the experimental objectives
• Analyze an experimental situation and identify the critical elements from a statistical point of view
• Establish a design of experiments in relation with the candidate models and the experimental constraints

Transversal skills

• Plan and carry out activities in a way which makes optimal use of available time and other resources.
• Use a work methodology appropriate to the task.
• Demonstrate the capacity for critical thinking
• Use both general and domain specific IT resources and tools

Teaching methods

This course combines theoretical instruction with practical exercises and a hands-on application project:

• Theoretical Presentation: Core concepts and principles are introduced through lectures and discussions.

• Case Calculations and Analysis: Students apply theoretical knowledge to solve exercises, reinforcing learning through calculation and critical analysis.

• Application Project: Each year, a unique project is assigned to the entire class.Students work in groups to complete the project collaboratively. Project sessions are scheduled as two-hour blocks every two weeks (effectively one hour per week, but condensed for deeper engagement).

This structure encourages active learning, teamwork, and the practical application of course concepts.

Expected student activities

• Synthesized the theoretical presentation in personal summary  with concept maps
• Solve exercise problems

Assessment methods

1/3 Imposed project prepared and reported in group of 3 students

2/3 Oral exam concisting in presenting individually the project (1/3) and answering theoretical question (1/3)

Resources

Bibliography

• Box, G.E.P.; Hunter, J.S.; Hunter, W.G. Statistics for Experimenters; Wiley Series in Probability and Mathematical Statistics, John Wyleyand Son, 1978.
• Montgomery, D.C. Design and analysis of experiments, 7th edition ed.; John Wyley and Son, 2009.
• Davison A.C.; Statistical model, Cambridge University Press in June 2003.
• Ryan Th.; Modern Experimental Design, John Wyley and Son, 2007.

Ressources en bibliothèque

• Find the references at the Library

Moodle Link

• https://go.epfl.ch/PHYS-442