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Arkistoitu opetussuunnitelma 2017–2019
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MTTTS13 Introduction to Bayesian Analysis 2 5 op
Organised by
Degree Programme in Mathematics and Statistics
Preceding studies
Recommended:
Corresponding course units in the curriculum
Informaatiotieteiden yksikkö
Curricula 2015 – 2017

Learning outcomes

After the course, the student will be able to apply Markov chains in statistical modelling and program the estimation of some simple models using Markov chain Monte Carlo methods. He will also be able to do model critique and comparison with Bayesian methods. Further, he will be able to perform the Bayesian analysis of some of the most commonly used statistical models.

Contents

Markov chains, MCMC methods, model checking and comparison, commonly used statistical models, such as hierarchical and regression models, binomial and count data models.

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Participation in course work 
In English
Option 2
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Written exam 
In English

Evaluation

Numeric 1-5.

Belongs to following study modules

Luonnontieteiden tiedekunta
2018–2019
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Luonnontieteiden tiedekunta