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Dette er studietilbudet for studieår 2020-2021.


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, MAT210 Real and Complex Calculus, 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
Jörn Schulz
Head of Department
Bjørn Henrik Auestad

Method of work

4 hours of problem solving per week, video-lectures

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

Mathematics and Physics - Bachelor's Degree Programme
Admission to Single Courses at the Faculty of Science and Technology
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Computer Science - Master's Degree Programme
Environmental Engineering - Master of Science Degree Programme
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Industrial Automation and Signal Processing - Master's Degree Programme - 5 year
Robot Technology and Signal Processing - Master's Degree Programme
Engineering Structures and Materials - Master's Degree Programme
Mechanical and Structural Engineering and Materials Science- Master's Degree Programme - 5 years
Mathematics and Physics - Master of Science Degree Programme
Mathematics and Physics, 5-year integrated Master's Programme
Offshore Field Development Technology - Master's Degree Programme
Industrial Asset Management - Master's Degree Programme
Master's Degree Programme - Marine- and Offshore Technology - 5 years
Marine- and Offshore Technology - Master's Degree Programme
Offshore Technology - Master's Degree Programme
Petroleum Geosciences Engineering - Master of Science Degree Programme
Petroleum Engineering - Master of Science Degree Programme
Petroleum Engineering - Master`s Degree programme in Petroleum Engineering, 5 years
Risk Analysis and Governance, International Master's degree Programme
Technical Societal Safety - Master's Degree Programme
Risk Management - Master's Degree Programme (Master i teknologi/siviling.)

Course assessment

Questionnaire and discussion with the students.

Literature


Link to reading list


Dette er studietilbudet for studieår 2020-2021.

Last updated: 15.08.2020