 | Study programme 2018-2019 | Français | |
 | Data Sciences II : analysis and modelling | ||
Activité d'apprentissage à la Faculty of Science |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) |
|---|---|---|---|
| S-BIOG-015 |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 15 | 0 | 15 | 0 | 0 | Q1 |
Content of Learning Activity
Multivariate statistics: PCA; factor analysis; hierarchical clustering; simple, polynomial and multiple regression.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable.
Other Recommended Reading
Barnier, J., 2018. Introduction à R et au tidyverse (https://juba.github.io/tidyverse/index.html). Ismay, Ch. & Kim A.Y, 2018. Moderndive: An introduction to statistical and data science via R (http://moderndive.com). Wickham, H. & Grolemund, G, 2017. R for data science (http://r4ds.had.co.nz). Zar, J.H., 2010. Biostatistical analysis (5th ed.). Pearson Education, London. 944pp. Husson, F., S. Lê & J. Pagès, 2009. Analyse de données avec R. Presses universitaires de Rennes, Rennes. 224pp. Cornillon, P.A. Et al, 2008. Statistiques avec R. Presses Universitaires de Rennes. 257pp. Dagnelie, P., 2007. Statistique théorique et appliquée, Volumes I et II (2ème ed.). De Boeck & Larcier, Bruxelles. 511pp (vol. I) 734pp (vol. II).
Mode of delivery
- Face to face
- Mixed
Type of Teaching Activity/Activities
- Cours magistraux
- Conférences
- Préparations, travaux, recherches d'information
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)