MET 270 Introduction to statistics and probability 2
Number of points (ECTS):
Course starts:
Teaching semester:
Final examination:
Course code:
10
Autumn
1
Autumn
MET 270
Faculty of Science and Technology
Department of Mathematics and Natural Science
Learning outcome
The students shall learn important basic skills in probability, statistics and stochastic process theory
and be able to use these skills on practical problems and in other courses.
After having completed the course one should:
•
Be able to use various probability distributions
•
Have basic knowledge of extreme value statistics.
•
Know about maximum likelihood estimation and have basic knowledge on estimation
•
Know of common models for stochastic processes.
•
Be able to do basic calculations for Poisson processes, Markov processes and renewal
processes
•
Have basic knowledge of Bayesian statistics
Contents
Basic issues in probability. Presentation of a number of commonly used probability distributions.
Short introduction to extreme-value statistic. Estimation, included the maximum likelihood principle,
in various situations. Stochastic processes, in particular Poisson processes, Markov processes and
renewal processes. Introduction to Bayesian statistics.
Prerequisites Thorough knowlegde in ÅMA110 or equivalent
Recommended prerequisites
Available for private candidates: No
Only available to students at
Master studies at the Faculty of Science and Technology.
Exams: Written exam
Student evaluation
Form and/or discussion
Method of work
Lectures and problem solving
Literature : To be announced at start of lectures