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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.

Contents

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.

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 exam1/14 hoursA - FNo 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.


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

Last updated: 12.12.2019