UE Biostatistics, Bioinformatics, Modeling , Part II

Diplômes intégrant cet élément pédagogique :


Course outline

 At the end of the course, the students should be able to analyze a "omic" dataset. More precisely, they should be able.

1- to load, explore and summarize graphically a dataset.

2- to compute confidence interval estimates for proportions, means and variances.

3- to formulate hypotheses, compute tests statistics, interpret p-values and make practical decisions for the standard parametric and non-parametric tests.

4- to adjust simple and multiple linear models, analyses of variance (anovas), logistic regression, Cox model.

5- to select genes that explain a response variable by applying multiple testing approaches.

6- to analyze a data set of differential gene expression.

Compétences visées

Overview of the principal techniques of statistical data treatment, with an emphasis on practical skills and the use of the statistical software R.

Informations complémentaires

Lieu(x) : Grenoble
Langue(s) : Anglais