Présentation

• Multiple regressions
• Generalized linear models
• Model selection
• Multivariate analysis (PCA, FA, PCoA, Hierarchical clustering)
• Multivariate regressions (PerMANOVA, CCA, RDA)
• Introduction to the analysis of microbial diversity.

Objectifs

To acquire good knowledge of fundamental and advance statistical tools in biology and microbial ecology. To learn how to implement statistical analysis with the software R.

Conditions d'admission

For BME Master Students: Course of Master 1 S2.

Not from Pau: Good level in biostatistics; To know the usual tests applied in environmental sciences (t-tests, correlations, ANOVA, simple and multiple regression, non-parametric tests)

Volume horaire

• Cours Magistral : 18h
• Travaux Dirigés : 18h

Examens

Courses spread all over the semester

Tutorials: Implementation of statistical analyses with the R software and case studies

Project: Analyses of datasets from the scientific literature (work in pairs).

50% final exam / 50% Project report