course-details-portlet

TMA4300 - Computer Intensive Statistical Methods

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation Weighting Duration Grade deviation Examination aids
Arbeider 30/100
Skriftlig eksamen 70/100 4 timer

Course content

Classical and Markov chain methods for stochastic simulation. Hierarchical Bayesian models
and inference in these. The expectation maximisation (EM) algorithm. Bootstrapping, cross-validation and non-parametric methods. Classification.

Learning outcome

1. Knowledge. The student knows computational intensive methods for doing statistical inference. This includes direct and iterative Monte Carlo simulations, as well as the expectation-maximisation algorithm and the bootstrap. The student has basic knowledge in how hierarchical Bayesian models can be used to formulate and solve complex statistical problems. Finally, the student understands a number of classification techniques.

2. Skills. The student can apply computational methods, such as Monte Carlo simulations, the expectation-maximisation algorithm and the bootstrap, on simple applied problems.

3. General competence. The student is able to give an oral presentation within the subject area.

Learning methods and activities

Lectures, works (projects) and student presentations of selected topics. Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination (70%) and works (projects) (30%). The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination. The lectures may be given in English. If the course is taught in English, the exam may be given only in English. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

  • Work
  • Student presentations

Course materials

Will be announced at the start of the course.

Credit reductions

Course code Reduction From To
SIF5085 7.5
Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2017

Language of instruction: English, Norwegian

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Subject area(s)
  • Statistics
  • Technological subjects
Contact information
Course coordinator:

Department with academic responsibility
Department of Mathematical Sciences

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Arbeider 30/100
Room Building Number of candidates
Spring ORD Skriftlig eksamen 70/100 2017-05-24 09:00
Room Building Number of candidates
Summer KONT Arbeider 30/100
Room Building Number of candidates
Summer KONT Muntlig eksamen 70/100 2017-08-14
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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