Objectives
– Demystifying Bayesian statistics and MCMC methods
– Differentiate between Bayesian and frequentist analyses
– Understanding the Methods section of a paper using Bayesian methods
– Implementing Bayesian analyses with R
Program :
– Bayesian inference: motivation and simple example
– Likelihood
– A detour through a priori distributions
– Markov chain Monte Carlo (MCMC) methods
– Bayesian analysis with R and the NIMBLE and brms software packages
– Generalized linear mixed models
https://oliviergimenez.github.io/statistique-bayes-quae/
At the end of the course, the learner will be able to carry out Bayesian statistical analyses with program R
https://oliviergimenez.github.io/statistique-bayes-quae/
Mixed format with lectures and practicals on computers
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