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.

Content

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.

Instruction

Lectures, exercises, seminars and laboratory sessions.

Assessment

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.