Course syllabus

Statistiska metoder för säkerhetsanalys
Statistical Methods for Safety Analysis

FMSF60, 7,5 credits, G2 (First Cycle)

Valid for: 2020/21
Decided by: PLED I
Date of Decision: 2020-04-03

General Information

Compulsory for: RH4-rh
Elective for: BME4, C4-sec, Pi4
Language of instruction: The course will be given in English on demand


The course presents notions and ideas from the foundations of a statistical treatment of risks. The emphasis lies on an understanding of the theory and methods presented. Hence the focus is put on applications within the field of risk and safety analysis.

Since in risks estimations one needs to combine information from different sources the Bayesian methods are frequently used in that area. Hence a reasonable proportion of the course is devoted to such approaches. In order to be able to analyse and predict frequencies of occurrences of hazardous scenarios, modern statistical tools, namely Poisson regression, analysis of deviance, extreme value theory and threshold methods are presented . The knowledge of such tools facilitates the understanding of the role of probability in risk analysis and proper use of outputs given by software packages.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must


A review of elementary concepts in probability theory; Independence, conditional probabilities, random variables, probability distribution functions, expected value, variance, covariance.

Presentation and simple applications of Bayes' Theorem, Central Limit Theorem, Law of Large Numbers and Law of Small Numbers.

Classical statistical inference; maximum likelihood method, confidence interval, hypotheses testing (goodness of fit tests). Introduction to bootstrap and the delta method to construct confidence intervals.

Introduction to Bayesian statistics; predictive probabilities, conjugated priors, credibility intervals.

Intensities, Poisson modelling; estimation, Poisson regression.

Some concepts from safety and reliability analysis, failure intensities, safety indexes, characteristic values.

Estimation of quantiles using POT-method.

Introduction to extreme values statistics. Estimation of design events, e.g. strength of 100 years storm, and uncertainty analysis of the estimates.

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written exam and compulsory computer exercises.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Code: 0117. Name: Examination.
Credits: 6,5. Grading scale: TH. Assessment: Written exam.
Code: 0217. Name: Laboratory Work.
Credits: 1. Grading scale: UG. Assessment: Computer exercises.


Admission requirements:

Assumed prior knowledge: Basic course in Mathematical Statistics or Statistics.
The number of participants is limited to: No
The course overlaps following course/s: FMS065

Reading list

Contact and other information

Director of studies: Johan Lindström,
Course homepage:
Further information: Changed course code from FMS065.