Statistiques
Coordinator :
Tom VAN DOOREN, Marie Laure MARTIN-MAGNIETTE and Tristan MARY-HUARD
ECTS :
Keywords :
statistical inference, likelihood, model selection, association studies.
Prerequisites for the course :
Know what random variables are, discrete and continuous distributions, quantiles, and other basic concepts in statistics.
Course objectives and description :
Biological data are often complex, with many interacting variables. Students are introduced to modelling data in general. Then they are made familiar with model selection among generalized linear models and mixed models, which are often used on datasets of small to intermediate size. After that, methods used on genome-wide data are discussed, as examples of large datasets occurring in biology. The course consists of lectures and computer exercises, used to make all participants acquainted with R statistical software. Students are expected to bring their own laptops and will analyse and discuss a real dataset.
Assessment / evaluation
: Computer project / exam
Course material (hand-outs, online presentation available, …) :
Not applicable
Suggested readings in relationship with the module content (textbook chapters, reviews, articles) :
Michael J. Crawley. Statistics : An Introduction using R. 2005. Pawitan Y. In All Likelihood : Statistical modeling and inference using likelihood. 2001. J. Daudin, S. Robin, and C. Vuillet. Statistique inférentielle : idées, démarche exemples, Presses Universitaires de Rennes ed., Société Française de Statistique, 1998. A range of documents is available from http://www.agroparistech.fr/Supports-de-cours,1177.html