Syllabus for Statistical Risk Analysis

Statistisk riskanalys

  • 5 credits
  • Course code: 1MS027
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Mathematics A1F, Technology A1F
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2010-05-11
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 24, 2019
  • Entry requirements: Applied Statistics or Probability Theory and Inference Theory.
    English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6").
  • Responsible department: Department of Mathematics

Learning outcomes

On completion of the course, the student should be able to:

  • use Bayesian methodology for estimating failure intensities and risks and evaluate the results;
  • formulate models where the Poisson process, in time or space, is used for modelling of rare events and related risks;
  • use basic methodology for statistical analysis of extreme values;
  • choose suitable statistical methodology for probabilistic risk analysis within applications from technology, the natural or social sciences.

Content

Conditional distributions. Bayesian methods for estimation of failure intensities and risks. The Poisson process and Poisson regression. Extreme-value analysis.

Instruction

Lectures, computersessions. Guest lecture. Case studies where the course content is applied in problems arising in technology, the natural or social sciences.

Assessment

Written examination at the end of the course (4 credits) combined with assignments during the course (1 credit). 
 
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Reading list

The reading list is missing. For further information, please contact the responsible department.