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This is the study programme for 2020/2021.


This course provides a foundation for problem solving in technology, science and economy using statistical modeling, simulation and analysis.

Learning outcome

After taking this course the student will:
  • be able to make and use statistical models for a number of problems in technology, natural science economy
  • have knowledge of the strengths and limitations of some key techniques for statistical modeling
  • be able to implement the models (in R)
  • carry out simulations of statistical models, analyze the results statistically, and be able to:
  • present results in a proper manner
  • make assessments of uncertainty in the results

Contents

The course focuses on methods to model and analyze a variety of random phenomena. The analysis will in practice often be done by simulation, but also the theoretical analysis is important. Students shall be able to implement statistical models on a computer, generate, interpret and present results. Topics that are appropriate to address: the general statistical model building, assessing the goodness of the model, estimation of distribution and parameters of the model and assess the uncertainty of estimates, bootstrap, number generators, variance reduction techniques, modeling and simulation of dependencies, modeling and simulation of stochastic processes. The course will have several exercises with the use of computers and the program R.

Required prerequisite knowledge

None.

Recommended previous knowledge

MAT100 Mathematical Methods 1, MAT200 Mathematical Methods 2, STA100 Probability and Statistics 1

Exam

Weight Duration Marks Aid
Portfolio with 3 individual written assignments1/1 A - FAll.
The first assignment counts 10%, the second assignment count 30% and the third assignment counts 60%. Course teacher sets final marks.
Candidates who fail on the assignments will not be able to submit new project assignments until the next time the course is taught.

Course teacher(s)

Course coordinator
Tore Selland Kleppe
Course teacher
Stein Andreas Bethuelsen, Jan Terje Kvaløy
Head of Department
Bjørn Henrik Auestad

Method of work

Six hours lectures and problem solving/data lab per week.

Overlapping courses

Course Reduction (SP)
Statistic modelling and simulation (TE6039_1) 5
Statistical modelling and simulation (MET260_1) 10

Open to

Mathematics and Physics - Bachelor's Degree Programme
Admission to Single Courses at the Faculty of Science and Technology
City and Regional Planning - Master of Science
Computer Science - Master's Degree Programme
Environmental Engineering - Master of Science Degree Programme
Industrial economics - Master's Degree Programme
Robot Technology and Signal Processing - Master's Degree Programme
Engineering Structures and Materials - Master's Degree Programme
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
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
Technical Societal Safety - Master's Degree Programme
Risk Management - Master's Degree Programme (Master i teknologi/siviling.)

Course assessment

Usually by forms and/or discussion according to university regulations.

Literature


Link to reading list


This is the study programme for 2020/2021.

Sist oppdatert: 14.08.2020