Practical sheet | REF: FIC1411 V1

Estimation of measurement bias using several methods.

Author: Morgan GERMA

Publication date: March 10, 2015 | Lire en français

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    5. Mistakes to avoid

    5.1 Don't forget the context of your measurements

    You may feel that your measurement results are accurate in relation to your internal standard, but you shouldn't be content with that. If your laboratory is found to be significantly different from other national laboratories (inter-laboratory tests on external standards), for example, you must try to understand the source of this discrepancy, so that you can correct it. That's why it's important to take part in interlaboratory tests, to ensure that your results are consistent when compared with those of other laboratories.

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