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