Discussing the main concepts of measurement uncertainty, practicing the estimation process. as per ISO/IEC 17025:2017

What you’ll learn

• Identify uncertainty sources and their contribution on uncertainty
• Master the terms used in measurement uncertainty
• Realise the different approaches that are used to estimate measurement uncertainty
• Estimate different types of uncertainties associated with different measurements
• understand the statistical treatment for the estimation process

Course content

2 total hours

Requirements

• Although no previous experience is required, Fair knowledge of spreadsheets would be very helpful to you.

Description

This is an introductory course on the estimation of measurement uncertainty. The course gives the main concepts and mathematical apparatus of measurement uncertainty estimation and introduces two principal approaches to measurement uncertainty estimation – the ISO GUM modeling approach (the “bottom-up” or modeling approach) and the single-lab validation approach as implemented by Nordtest (the “top-down” or Nordtest approach). The course contains lectures and practical exercises.

Course Structure:

•Introduction and essential terminology.

•Concept of measurement uncertainty.

•Basic definitions.

•Probability distribution functions.

•Basic statistics.

•Quantifying measurement uncertainty

•Bottom-up approach.

•uncertainty sources.

•Estimating standard, combined and expanded uncertainties.

•Practice the quantification process for standards and real life examples.

•Top-down approach.

•uncertainty sources.

•Estimating standard, combined and expanded uncertainties.

•Practice the quantification process for standards and real life examples.

Study outcomes

The student who has successfully passed the course knows:

• the main concepts related to measurement results and measurement uncertainty, including their application to chemical analysis;

• the main mathematical concepts and tools in uncertainty estimation;

• the main measurement uncertainty sources in chemical analysis;

• the main approaches for measurement uncertainty estimation.

The student who has successfully passed the course is able to:

• decide what data are needed for uncertainty estimation, understand the meaning of the available data and decide whether the available data are sufficient;

• select the uncertainty estimation approach suitable for the available data;

• quantify the uncertainty contributions of the relevant uncertainty sources using the available data;

• carry out estimation of uncertainty using the main approaches of uncertainty estimation.

Who this course is for:

• Staff of Quality control and Quality assurance QC/QA
• Laboratory chemists
• medical Laboratory staff
• Post graduate researcher
• ISO 17025 and ISO 15189 interested personnel.

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