Decision Theory, 6 credits

Beslutsteori, 6 hp

732A66

Main field of study

Statistics

Course level

Second cycle

Course type

Single subject and programme course

Examiner

Anders Nordgaard

Course coordinator

Anders Nordgaard

Director of studies or equivalent

Jolanta Pielaszkiewicz
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Weeks Language Campus ECV
F7MSL Statistics and Machine Learning, Master´s Programme - First and main admission round 3 (Autumn 2021) 202135-202202 English Linköping E
F7MSL Statistics and Machine Learning, Master´s Programme - Second admission round (open only for Swedish/EU students) 3 (Autumn 2021) 202135-202202 English Linköping E

Main field of study

Statistics

Course level

Second cycle

Advancement level

A1N

Course offered for

  • Master's Programme in Statistics and Machine Learning

Entry requirements

  • Bachelor's degree equivalent to a Swedish Kandidatexamen of 180 ECTS credits in one of the following subjects:
    • statistics
    • mathematics
    • applied mathematics
    • computer science
    • engineering
  • Completed courses in
    • calculus
    • linear algebra
    • statistics
    • machine learning
    • programming
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6/B)
    (Exemption from Swedish

Intended learning outcomes

After completion the course, the student should on an advanced level be able to:
- use statistical methods for decision making,
- apply the principles for subjective probability interpretation, Bayesian inference, utility theory and sequential analysis in order to make a decision,
- critical assess the presumptions for each step in a decision making process

Course content

The course content comprises:
- The subjective interpretation of probabilities 
- Probabilistic reasoning and likelihood theory,
- Bayesian hypothesis evaluation,
- Decision theoretic elements
- Utility and loss functions
- Graphical modelling as a tool for decision making
- Sequential analysis

Teaching and working methods

Assignments encompassing both theoretical and computer-based exercises. One final oral examination.
Detailed information about the examination can be found in the course’s study guide. 

Examination

Assignments encompassing both theoretical and computer-based exercises. One final oral examination.
Detailed information about the examination can be found in the course’s study guide. 

Grades

ECTS, EC

Department

Institutionen för datavetenskap
Code Name Scope Grading scale
TENT Examination 3 credits EC
UPG1 Exercise 3 credits EC
There is no course literature available for this course in studieinfo.

This tab contains public material from the course room in Lisam. The information published here is not legally binding, such material can be found under the other tabs on this page.

There are no files available for this course.