Probability and Statistics 2 - Study courses

Dette er studietilbudet for studieår 2019-2020. Endringer kan komme.

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, STA100 Probability and Statistics 1

Exam

	Weight	Duration	Mark	Supporting materials
Written exam	1/1	4 hours	A - F	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: Tore Selland Kleppe
Course teacher: Tore Selland Kleppe
Head of Department: Bjørn Henrik Auestad

Method of work

4 hours lectures and 2 hours problem solving per week.

Overlapping courses

Course	Reduction (credits)
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 to

Master studies at the Faculty of Science and Technology and Bachelorstudents in mathematics and physics.

Course assessment

Questionnaire and discussion with the students.

Literature

Walpole, Myers, Myers and Ye. "Probability and Statistics for Engineers and Scientists", 9. edition, Pearson.