Probability and Statistics 2 (STA500)
Basic and advanced issues in probability, statistical modeling using stochastic processes, estimation and statistical inference.
Course description for study year 2025-2026
Course code
STA500
Version
1
Credits (ECTS)
10
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
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 method, 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. Use of software (R).
Learning outcome
After having completed the course, the student 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
Recommended prerequisites
or equivalent courses.
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Written exam | 1/1 | 4 Hours | Letter grades | Approved, basic calculator, One A4 sheet of handwritten notes, |
Permitted aids on the exam are simple approved calculator and one A4-sheet with your own handwritten notes. It is allowed to write on both sides of the note sheet, and the notes should be written by hand directly on the sheet.Written exam is with pen and paper
Coursework requirements
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 SchulzCourse coordinator:
Jan Terje KvaløyHead of Department:
Bjørn Henrik AuestadMethod of work
4+2 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 |
