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University of Gothenburg
Computational Methods for Bayesian Statistics
<p>The course gives an introduction to Bayesian statistical modelling and inference, focusing on computational methods such as Markov chain Monte Carlo (McMC) and other simulation methods, but also looking at tools such the EM algorithm. We emphasize the interplay between statistical modeling and applied problem sol…
- Higher education
- Information unavailable
- 2 September 2024
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>The course gives an introduction to Bayesian statistical modelling and inference, focusing on computational methods such as Markov chain Monte Carlo (McMC) and other simulation methods, but also looking at tools such the EM algorithm. We emphasize the interplay between statistical modeling and applied problem solving, as well as computational and theoretical aspects of the models.</p>
Admission scores
Entry requirements
Basic skills in mathematical statistics. Basic skills in scientific programming (for example in Matlab or R) as achieved by completing MSG400 "Stochastic Data Processing and Simulation".
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2024-09-02
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.msa102.11758.20242
- Last checked
- 2026-09-23T10:36:59.285029+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
Application and important dates
- Programme or course starts
- Programme or course ends
Salary and salary distribution
Common occupations after graduation
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Geographical background
Previous upper-secondary schools and programmes
Completion and outcomes
About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.gu.msa102.11758.20242
- Offering identity in the source
- e.uoh.gu.msa102.11758.20242
- Education-form source code
- HS
- Education code in the source
- MSA102
- Change time according to the source
- 2024-09-06T13:02:54
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.