 | Study programme 2019-2020 | Français | |
| Analysis of Experimental Data | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-MARO-156 |
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|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 30 | 12 | 0 | 0 | 0 | Q2 |
| Organisational online arrangements for the end of Q3 2019-2020 assessments (Covid-19) |
|---|
|
Content of Learning Activity
data representation and analysis; factorial methods (principal components analysis, multiple correspondance methods, rank analysis, ...); regression, analysis of variance; classification, clustering, experimental design. Software : R, Weka
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
I. H. Witten, E. Frank. Data Mining : "Practical Machine Learning Tools and Techniques with Java Implementations". Morgan Kaufmann, 2010
J-M. Azaïs, J-M. Bardet, "Le Modèle Linéaire par l'exemple : Régression, Analyse de la Variance et Plans d'Expériences. Illustrations numériques avec les logiciels R, SAS et Splus", Dunot, 2006
R.E.Walpole, R.H.Myers, S.L.Myers, K.Ye, "Probability and Statistics for Engineers and Scientists", Prentice Hall, 2012
Mode of delivery
- Face to face
Type of Teaching Activity/Activities
- Cours magistraux
- Ateliers et projets encadrés au sein de l'établissement
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)