Special Students "University of Zurich (UZH)" in the Master Program in Biostatistics at UZH cannot register for this course unit electronically. Forward the lecturer's written permission to attend to the Registrar's Office. Alternatively, the lecturer may also send an email directly to firstname.lastname@example.org. The Registrar's Office will then register you for the course.
Bayes statistics is attractive, because it allows to make decisions under uncertainty where a classical frequentist statistical approach fails. The course provides an introduction into bayesian methods. It is moderately mathematically technical, but demands a flexibility of mind, which should not underestimated.
conditional probability; bayes inference (conjugate distributions, HPD-areas; linear and empirical bayes); determination of the a-posteriori distribution through simulation (MCMC with R2Winbugs); introduction to multilevel/hierarchical models.
Gelman A., Carlin J.B., Stern H.S. and D.B. Rubin, Bayesian Data Analysis, Chapman and Hall, 2nd Edition, 2004.
Kruschke, J.K., Doing Bayesian Data Analysis, Elsevier2011.
Prerequisites / Notice
Prerequisite:Basic knowledge of statistics; Knowledge of R.