In the course, the PhD students will be introduced to Bayesian hierarchical modelling, which are becoming increasingly popular for fitting ecological, environmental, and human disease models to temporal and spatial data. The aim of the course is to introduce the students to i) the applied use of likelihood functions and Bayesian statistics, ii) setting up advanced hierarchical statistical models with latent variables, iii) applying advanced statistical models, and iv) making quantitative predictions with a known degree of uncertainty.