Yves-Laurent Grize: Catalogue data in Autumn Semester 2020

NameMr Yves-Laurent Grize
DepartmentMathematics
RelationshipLecturer

NumberTitleECTSHoursLecturers
447-6273-00LBayes Methods Restricted registration - show details
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 Link. The Registrar's Office will then register you for the course.
2 credits2GY.‑L. Grize
Abstractconditional 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.
Objective
ContentBayes 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.
LiteratureGelman 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 / NoticePrerequisite:Basic knowledge of statistics; Knowledge of R.