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Introduction to Bayesian data analysis for social and behavioural sciences using R and Stan (BDRS01)
3rd December 2018 - 7th December 2018
This course provides a general introduction to Bayesian data analysis using R and the Bayesian probabilistic programming language Stan. We begin with a gentle introduction to all the fundamental principles and concepts of Bayesian data analysis: the likelihood function, prior distributions, posterior distributions, high posterior density intervals, posterior predictive distributions, marginal likelihoods, Bayes factors, etc. We will do this using some simple probabilistic models that are easy to understand and easy to work with. We then proceed to more practically useful Bayesian analyses, starting with general linear models, followed by generalized linear models, including logistic regression and Poisson regression, followed by multilevel general and generalized linear models. For these analyses, we will use real world data sets, and carry out the analysis with Stan using the brms interface to Stan in R. With each example, we will explore general concepts such as model checking and improvement using posterior predictive checks, and model evaluation using cross-validation, WAIC, and Bayes factors. In the final part of the course, we will delve into some more advanced topics: understanding Markov Chain Monte Carlo in depth, Gaussian process regression, probabilistic mixture models.
To find out more or to book online via our sister company (PS statistics) use the link below…
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)