Probability and Statistics 2 (STA500)
Basic issues in probability. Presentation of a number of commonly used probability distributions. Short introduction to extreme-value statistic. Estimation, in particular the maximum likelihood principle,and confidence intervals in various situations. Brief introduction to Bayesian statistics. Introduction to stochastic processes, in particular Poisson processes and Markov processes. Theory and areas for applications of the various methods will be covered.
Course description for study year 2022-2023
Facts
Course code
STA500
Version
1
Credits (ECTS)
10
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
Time table
Content
Basic issues in probability. Presentation of a number of commonly used probability distributions. Short introduction to extreme-value statistic. Estimation, in particular the maximum likelihood principle,and confidence intervals in various situations. Brief introduction to Bayesian statistics.Stochastic processes, in particular Poisson processes and Markov processes. Theory and areas for applications of the various methods will be covered.
Learning outcome
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 about estimation and confidence intervals
- Have basic knowledge of Bayesian statistics
- Know of common models for stochastic processes.
- Be able to do basic calculations for Poisson processes and Markov processes, including simple queue models.
Required prerequisite knowledge
None
Recommended prerequisites
MAT100 Mathematical Methods 1, MAT200 Mathematical Methods 2, MAT210 Real and Complex Calculus, STA100 Probability and Statistics 1
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Written exam | 1/1 | 4 Hours | Letter grades | No printed or written materials are allowed. Approved basic calculator allowed |
Coursework requirements
Mandatory submissions
At least 8 out of 12 exercises must be submitted and recieve a pass in order to be eligable to take the exam.
Course teacher(s)
Course coordinator:
Jörn SchulzHead of Department:
Bjørn Henrik AuestadMethod of work
6 hours of lectures and problem solving per week, self study.
Overlapping courses
| Course | Reduction (SP) |
|---|---|
| Mathematical statistics and stochastic processes A (MOT100_1) | 7 |
| Mathematical statistics and stochastic processes B (MOT110_1) | 4 |
| Mathematical statistics (MOT150_1) | 4 |
| Mathematical Statistics - Petroleum (MOT320_1) | 4 |
| Introduction to Statistics and Probability 2 (MET270_1) | 10 |
| Stochastic modeling (TE6517_1) | 4 |
| Stochastic modeling (TE6517_A) | 4 |
Open for
Course assessment
Questionnaire and discussion with the students.