7.5 credits cr.
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A course on Bayes' formula and posterior distributions.
The course covers Bayes' formula, informative and non-informative prior distributions, posterior distributions, single- and multiparameter distributions like binomial, multinomial och normal distributions, hierarchical models, linear models, Bayesian inference and goodness-of-fit measures and stochastic simulation with MCMC (Markov Chain Monte Carlo).
The course consists of one element.
The education consists of lectures, exercises and computer exercises.
The course is assessed through written examination.
A list of examiners can be found on
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
Course literatureNote that the course literature can be changed up to two months before the start of the course.