• Oct 6, 2021 to Oct 7, 2021
  • Location: LGC, Queens Road, Teddington, Middlesex, TW11 0LY
  • Latest Activity: Jul 14, 2021

Whenever a measurement is made there will always be some uncertainty about the result due to unavoidable errors in the measurement process. Knowledge of this uncertainty allows a judgement to be made as to whether the data are likely to be ‘fit for purpose’. 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 and includes laptop-based workshops using Excel.

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
  • Apply statistical principles through laptop-based workshops.

CLASSROOM BASED COURSES

Classroom based course are delivered over two days. If the course you have been booked on cannot be delivered we will offer you the option to attend remotely if possible, or we will transfer you to the next date. If neither of these options are suitable we will provide a refund of any course fees paid. Download the course programme

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.

Find out more here

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