Description

Objectives in terms of knowledge (course content) :

• criteria to build the most efficient plan, according to the biological context
• the role of experimental uncertainties in a plan
• a model to build the plan and the plan to build a model
• single and multiple linear regressions in the context of optimization processes
• model validation
• confidence and prediction intervals

• Reminder of the main analytical tools used for experimental design and image processing (jointly presented during the first lectures)
• a unique matrix tool to represent both images and plans: definition and elementary calculations
• projection and dimensionality reduction
• decomposition into simple elements
• solving under-parametrized systems

Compétences visées

Objectives in terms of acquired skills :
The student will be able to efficiently build basic experimental plans, to perform data analysis in the context of optimization processes, and to understand publications that are using experimental design, specially in the production field.
 

Contacts

Responsable(s) de l'enseignement

• Yves Nominé

MCC

Les épreuves indiquées respectent et appliquent le règlement de votre formation, disponible dans l'onglet Documents de la description de la formation.

Régime d'évaluation

CT (Contrôle terminal, mêlé de contrôle continu)

Coefficient

1.5

Évaluation initiale / Session principale - Épreuves

Seconde chance / Session de rattrapage - Épreuves