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STAT-F428

Bayesian Statistics

academic year
2025-2026

Course teacher(s)

Maarten JANSEN (Coordinator)

ECTS credits

5

Language(s) of instruction

english

Course content

  1. The Bayesian approach, introduction: information and uncertainty, the central role of Bayes'rule in sequential learning
     
  2. Bayes estimators, loss and risk, Bayesian decision rules, admissible decisions
     
  3. Choosing the prior: Fisher information, Kullback-Leibler divergence, Shannon entropy, uninformative priors (uniform, Jeffrey's, Maxent, reference), improper priors, conjugate priors
     
  4. applications

Objectives (and/or specific learning outcomes)

The goal is to acquire familiarity with Bayesian reasoning, appreciate benefits and drawbacks, compared to frequentist statistics
 

Prerequisites and Corequisites

Required and Corequired knowledge and skills

Basic concepts of probability theory and statistics
 

Teaching methods and learning activities

Face to face teaching with illustrations and exercises
 

References, bibliography, and recommended reading

See material on Université Virtuelle
 

Other information

Campus

Plaine

Evaluation

Method(s) of evaluation

  • written examination
  • Other

written examination

  • Open book examination
  • Open question with short answer

Other

Language(s) of evaluation

  • english

Programmes