Introduction to Bayesian Statistics Using R and Stan for Ecologists
The course offers a straightforward and practical approach to applied statistics using Bayesian inference. It starts with a gentle introduction to the concepts of Bayesian statistics (priors, likelihood, posterior distribution, MCMC). Based on many examples, the main focus is the discussion and coding of ecological models, step-by-step from basic ANOVA or linear regression to nonlinear models.
Didactic aims/ competencies gained
Participants learn how to practically think in terms like data, model, likelihood, parameters, predictions. They learn how to specify and code their own models of varying complexity in R.
Prior knowledge needed
Basic knowledge in R and statistics, e.g. loading and transforming data, performing basic linear regression using lm.
Participants are expected to participate actively in the hands-on training and to bring their own laptops.