Syllabus for Statistics for Engineers

Statistik för ingenjörer

A revised version of the syllabus is available.


  • 5 credits
  • Course code: 1MS008
  • Education cycle: First cycle
  • Main field(s) of study and in-depth level: Mathematics G1F
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2008-03-18
  • Established by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2008
  • Entry requirements:

    Calculus for Engineers, Algebra and Vector Geometry

  • Responsible department: Department of Mathematics

Learning outcomes

In order to pass the course (grade 3) the student should

  • know a number of methods and techniques for visualisation of data sets;

  • be able to compute probabilities in simple cases;

  • have a basic knowledge of stochastic variables and some common probability distributions;

  • understand the meaning of the central limit theorem;

  • have developed an intuitive understanding of randomness and random behaviour;

  • understand the use of point and interval estimates for some typical statistical problems;

  • know the method of regression for fitting measured data;

  • be aware of some typical engineering applications of probability and statistics, e.g. reliability and quality control.


    Descriptive statistics: measures of location and variation, frequency tables, bar diagrams, histograms, other diagrams and tools for visualisation. Introductory combinatorics and probability theory. Probability distributions: binomial, Poisson, normal, exponential. Central limit theorem. Point and interval estimation. The method of regression. Engineering applications, selected examples.


    Lectures and problem solving sessions.


    Written examination at the end of the course. Moreover, compulsory assignments may be given during the course.

  • Reading list

    Reading list

    Applies from: Autumn 2009

    Some titles may be available electronically through the University library.

    Reading list revisions

    Last modified: 2022-04-26