 | Study programme | Français | |
 | Applied Statistics | ||
Programme component of Master's Degree in Computer Science à la Faculty of Science |
| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-M1-SCINFO-022-M | Optional UE | GROSJEAN Philippe | S807 - Ecologie numérique des milieux aquatiques |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Français | 15 | 0 | 15 | 0 | 0 | 3.00 | 100.00 |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
|---|---|---|---|---|---|---|---|---|
| S-INFO-032 | Applied Statistics | 15 | 0 | 15 | 0 | 0 | Q1 | 100.00% |
| Unité d'enseignement |
|---|
Objectives of Programme's Learning Outcomes
- Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
- Develop and integrate a high degree of autonomy.
- Develop and integrate a high degree of autonomy to evolve in new contexts.
Learning Outcomes of UE
To be able to analyze correctly biological data with time-dependencies, to fit a nonlinear model (cinetic curve, growth model, dose-response curve, etc.) and to find useful information in a large dataset using data mining tools.
Content of UE
Space-time series; machine learning; random forest; discriminant analysis; nonlinear regression; growth model; doe-response curve; Von Bertallanffy; Richards; Weibull; Gompertz; R software.
Prior Experience
Basic statistics.
Type of Assessment for UE in Q1
- Oral examination
Q1 UE Assessment Comments
Preparation of a theoretical subject, or based on a partly solved dataset during 1/2h. Discussion around this question (explanation of the method, what to do next, others methods appliable on such data, etc.)
Type of Assessment for UE in Q2
- Oral Examination
Q2 UE Assessment Comments
Preparation of a theoretical subject, or based on a partly solved dataset during 1/2h. Discussion around this question (explanation of the method, what to do next, others methods appliable on such data, etc.)
Type of Assessment for UE in Q3
- Oral examination
Q3 UE Assessment Comments
Preparation of a theoretical subject, or based on a partly solved dataset during 1/2h. Discussion around this question (explanation of the method, what to do next, others methods appliable on such data, etc.)
Type of Resit Assessment for UE in Q1 (BAB1)
- Oral examination
Q1 UE Resit Assessment Comments (BAB1)
Preparation of a theoretical subject, or based on a partly solved dataset during 1/2h. Discussion around this question (explanation of the method, what to do next, others methods appliable on such data, etc.)
Type of Teaching Activity/Activities
| AA | Type of Teaching Activity/Activities |
|---|---|
| S-INFO-032 |
|
Mode of delivery
| AA | Mode of delivery |
|---|---|
| S-INFO-032 |
|
Required Reading
| AA | |
|---|---|
| S-INFO-032 |
Required Learning Resources/Tools
| AA | Required Learning Resources/Tools |
|---|---|
| S-INFO-032 | Not applicable |
Recommended Reading
| AA | |
|---|---|
| S-INFO-032 |
Recommended Learning Resources/Tools
| AA | Recommended Learning Resources/Tools |
|---|---|
| S-INFO-032 | Venables W.N. & B.D. Ripley, 2002. Modern applied statistics with S-PLUS (4th ed.). Springer, New York, 495 pp. |
Other Recommended Reading
| AA | Other Recommended Reading |
|---|---|
| S-INFO-032 | Legendre, P. & L. Legendre, 1998. Numerical ecology (2nd ed.). Springer Verlag, New York. 587 pp. Pinhero, J. C. & D. M. Bates, 2000. Mixed-effects models in S and S-PLUS. Springer, New York. 528 pp. Zar, J.H., 2010. Biostatistical analysis (5th ed.). Pearson Education, London. 944pp. |
Grade Deferrals of AAs from one year to the next
| AA | Grade Deferrals of AAs from one year to the next |
|---|---|
| S-INFO-032 | Autorisé |