In this course, the problem of uncertainty evaluation is formulated as one of propagating probability distributions through a measurement model. It explores three approaches to finding the best estimate of the measurand and the associated measurement uncertainty that are all consistent with the ‘Guide to the expression of uncertainty in measurement’ (GUM):

• The GUM uncertainty framework
• A Monte Carlo method
• Analytical methods

The course concludes by considering whether the different approaches to uncertainty evaluation give the same result, and by introducing a validation procedure that helps to identify which method is most appropriate for a particular measurement situation.

You may have seen one approach, the GUM uncertainty framework, in our e-learning course ‘Understanding Uncertainty Budgets’. We strongly recommend that you are familiar and confident with the content of ‘Understanding Uncertainty Budgets’ before enrolling in this course.

This course consists of seven modules:

• Module 1: Evaluating measurement uncertainty
• Module 2: Using probability distributions to characterise quantities
• Module 3: The formulation stage
• Module 4: The GUM uncertainty framework
• Module 5: A Monte Carlo method
• Module 6: An analytical approach
• Module 7: Choosing a solution approach

Learners who successfully complete the course will receive an NPL Certificate of Completion.