Study programme | Français | ||
Applied Biostatistics | |||
Programme component of Master's Degree in Biochemistry and Molecular and Cell Biology à la Faculty of Science |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
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US-M1-SCBBMC-004-M | Compulsory UE | GROSJEAN Philippe | S807 - Ecologie numérique des milieux aquatiques |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
---|---|---|---|---|---|---|---|---|---|
| Français | 15 | 15 | 0 | 0 | 0 | 3.00 | 100.00 |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
---|---|---|---|---|---|---|---|---|
S-BIOG-025 | Applied Biostatistics | 15 | 15 | 0 | 0 | 0 | Q1 | 100.00% |
Unité d'enseignement |
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Objectives of Programme's Learning Outcomes
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
General uni- and multivariate statistics.
Type of Assessment for UE in Q1
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.)
Q2 UE Assessment Comments
Not applicable
Type of Assessment for UE in Q3
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)
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 |
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S-BIOG-025 |
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Mode of delivery
AA | Mode of delivery |
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S-BIOG-025 |
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Required Reading
AA | |
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S-BIOG-025 |
Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
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S-BIOG-025 | Not applicable |
Recommended Reading
AA | |
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S-BIOG-025 |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
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S-BIOG-025 | 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 |
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S-BIOG-025 | 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 |
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S-BIOG-025 | Autorisé |