Evaluating measurement uncertainty for chemical testing laboratories
- 2 days
06 Mar 2018
06 Jun 2018
17 Oct 2018
Measurements are always made for a reason – to answer a particular question or to help solve a problem. Whenever a measurement is made there will always be some uncertainty about the result due to unavoidable errors in the measurement process. Knowledge of the uncertainty associated with measurement results allows a judgement to be made as to whether the data are likely to be ‘fit for purpose’. If comparisons of results are being made, for example when determining whether a limit has been exceeded, a meaningful interpretation of the results can only be achieved if the uncertainty is known. The evaluation of the uncertainty associated with measurement results is a requirement for testing laboratories accredited to ISO/IEC 17025. This course provides a practical approach to evaluating uncertainty in testing laboratories which is in line with the ISO principles for uncertainty estimation and current accreditation requirements. The course assumes no prior knowledge of uncertainty evaluation.
Download the course programme.
What are the benefits?
This course will help you:
- Understand how uncertainty can be evaluated for chemical test results
- Use method validation and quality control data in uncertainty estimates
- Give your customers confidence in your results
- Determine the fitness for purpose of your results
- Demonstrate compliance with regulatory limits and contract specifications
- Make valid comparisons between results obtained at different times and places
- Meet ISO/IEC 17025 accreditation requirements.
The course will cover:
Day 1 – The Principles
- Introduction to the concept of measurement uncertainty
- Statistics for measurement uncertainty estimation
- The basic principles of evaluating uncertainty
- Converting data and combining uncertainties
- Quantifying uncertainty components
- Evaluation of an uncertainty budget using spreadsheets
- How to handle precision.
Day 2 – The Practice
- Using data from validation studies
- Cause and effect analysis
- Dealing with data from recovery estimations
- Using precision data from validation studies
- Handling uncertainty for large concentration ranges
- Using and conveying uncertainty estimates.
Who should attend?
The course is aimed at analysts who have limited knowledge of measurement uncertainty but need to be able to evaluate the uncertainty associated with their results.