NMAK16002U  Bayesian Statistics

Volume 2018/2019
Education

MSc Programme in Statistics

MSc Programme in Mathematics-Economics 

Content
  • The Bayesian paradigm
  • Sufficiency and likelihood
  • Prior and posterior distributions
  • Decision theoretic foundations
  • Bayesian parameter estimation
  • Tests and confidence regions
  • Bayesian calculations and Monte Carlo methods
  • Bayes factors and model choice
  • Empirical Bayes methods
Learning Outcome

Knowledge:

Basic knowledge of the topics covered

Skills:

  • Discuss and understand basics of the Bayesian paradigm
  • Understand how decision theory underpins Bayesian inference
  • Understand methods for constructing prior distributions
  • Discuss and understand basic principles for Bayesian model choice

 

Competences:

  • Ability to use software for modelling and Bayesian computation
  • Ability to perform Bayesian analysis of statistical models

 

Basic understanding of mathematical statistics including conditional distributions. Stat1 + Stat2 or equivalent is sufficient.
Lectures and theoretical exercises
Identical to NMAK16002U Bayesian Statistics.
Credit
7,5 ECTS
Type of assessment
Written assignment, 27 hours
Written assignment
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

As for the ordinary exam

Criteria for exam assesment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

  • Category
  • Hours
  • Lectures
  • 28
  • Exercises
  • 21
  • Exam
  • 27
  • Preparation
  • 130
  • Total
  • 206