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During Control 2019, Hitachi High-Tech’s Anne Wegner, EMEA Applications Manager, presented on ‘The quest for the true value: How do I judge analytical data and measurement uncertainty’.

In spectroscopy amongst others, measurements are prone to errors. Even worse, the true value is unknown. So it’s of great importance to estimate the error in a measurement in relation to the expected value and specify it in the results.

The result “carbon content is 0.13345 %“ is incomplete without specification of the uncertainty in measurement and can’t be compared to other results. Equally many decimal places in the results can lead to the belief of accuracy, which would not be if the uncertainty in measurement would be considered.

Here’s what you’ll learn

  • Basics and definitions
  • Statistics
  • Measurement uncertainty according to GUM
  • Application

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