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Elements of Statistical Modelling


The aim consists in making students aware of practical problems requiring stochastic
modelling of observations and to introducing them to the generalized linear model
(variable selection, tests, ...)
At the end of this module, the student should be able to:
- explain the characteristics of the generalized linear model
- propose an algorithm to calculate or approximate the maximum
likelihood estimator
- validate the chosen model (variable selection, tests, ...)
- perform a complete statistical analysis on a real data set.

Needed prerequisite

Statistical inference (3rd and 4th year).

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...