Statistical Quality Control

5 credits

Syllabus, Bachelor's level, 1TG286

A revised version of the syllabus is available.
Education cycle
First cycle
Main field(s) of study and in-depth level
Industrial Engineering and Management G1F
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 8 October 2021
Responsible department
Department of Civil and Industrial Engineering

Entry requirements

Participation in courses of 15 credits in industrial engineering and management. Participation in Quality Management 10 credits.

Learning outcomes

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

  • give an account of the concept of probability,
  • apply different position and dispersion measures,
  • present statistical information in different forms,
  • critically analyse the use of statistics and diagrams,
  • carry out basic probability calculations and analyses on normally, binomially, Poisson and exponentially distributed data,
  • identify and handle different types of variation,
  • apply quality controls for normally distributed data,
  • give an account of the aim of experimental design and be able to carry out complete factor experiments.


Position and dispersion measures, probabilities, visualisation using different diagrams. Normal, binomial, Poisson and exponential distribution. Statistical quality management, quality controls, capability and the basics of experimental design, and computer-supported data management and calculations.


Lectures, exercises, seminars and laboratory sessions.


Written assignments and laboratory sessions (3 credits). Written examination (2 credits).

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 targeted pedagogical support from the University's disability coordinator.

Other directives

The course cannot be included in the same degree as 1TG259 Applied Variation and Statistics in Quality Development.