MTTTS13 Introduction to Bayesian Analysis 2 5 ECTS
Period I Period II Period III Period IV
Language of instruction
Type or level of studies
Advanced studies
Course unit descriptions in the curriculum
Degree Programme in Mathematics and Statistics
Faculty of Natural Sciences

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.

Enrolment for University Studies

Enrolment time has expired


Hyon-Jung Kim-Ollila, Teacher responsible


22-Oct-2018 – 14-Dec-2018
Mon 22-Oct-2018 - 10-Dec-2018 weekly at 12-14, LS B4125, Pinni B
29-Oct-2018 at 12 –14 , LS B0016, Pinni B
12-Nov-2018 at 12 –14 , ML 7, TietoPinni
19-Nov-2018 at 12 –14 , LS B0020, Pinni B
Wed 24-Oct-2018 - 12-Dec-2018 weekly at 12-14, LS B4115, Pinni B
Midterm exam
Wed 28-Nov-2018 at 12-16, ML 7, TietoPinni
Final exam
Wed 12-Dec-2018 at 12-16, LS B1083, Pinni B
Wed 24-Oct-2018 - 12-Dec-2018 weekly at 14-16, LS B4116, Pinni B