Objectives:

• Introduction to R variables, data types and graphical output;
• Simulate evolution of populations;
• Exploratory analysis for ecology and evolution (PCA, MDS, etc.);
• Linear regression, ANOVA and hypothesis testing using resampling techniques (bootstrap, permutations, etc.);
• Bayesian statistics: advanced inference algorithms (Markov chain Monte Carlo);
• Student’s case studies.

Date: February 11th, 2019 to February 15th, 2019
Deadline for Applications: January 11th, 2019