- Define rigorously a notion seen in the course; give a geometrical interpretation of it; explain in which fields of application it is found (precise examples). - Be able to interpret and manipulate a mathematical formula; demonstrate mathematical properties. - From a problem situation, isolate the data and unknowns; model; represent the situation; solve the problem; interpret the results; judge their plausibility. - Apply without hesitation the techniques appropriate to the solution of numerical problems related to the subjects taught.
This course addresses mathematics as a discipline serving the biological sciences, and in particular the statistics course. In this sense, it will zoom in on certain mathematical notions used in statistics (elementary calculation, sum symbol, set elements, matrices, functions of two variables, etc.) and will develop its mathematical components. The mathematics covered has a dual purpose: to complement the mathematics of the statistics course and to provide a general mathematical culture to tackle certain problems (e.g. problems of optimisation of functions in two variables).
Some elements of mathematical language are introduced to facilitate the understanding of statistics courses (sum symbol, set theory, predicate logic). We then introduce functions of several variables and we tackle optimization problems in two variables. The course ends with matrix algebra, including the presentation of Leslie matrices.
Formula: written examination offered in January and August. The assessment will consist of a written examination including both exercises and theory (in particular demonstrations of the properties covered). The difficulty of the exercises will be comparable to that of the exercises presented in the course and in tutorials. An assessment will be organised in January (first session) and August (second session). The use of a calculator is not allowed. If the exam is done online (distance learning), an update of the proposed formula may take place.
Course syllabus; Biau G., Droniou J., Herzlich M. Mathématiques et statistique pour les sciences de la nature. Modéliser, comprendre, appliquer, EDP Sciences, Collection enseignement sup, Mathématiques, Paris, 2010. Dupiereux E., De la variabilité aux risques d'erreurs. Presses universitaires de Namur, Namur, 2013.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Bachelor in Biology | Standard | 0 | 3 | |
| Bachelor in Biology | Standard | 2 | 3 |