Should Gabriel visit Maria? A short introduction to Bayes’ Theorem
Content
The interpretation of the result of a qualitative analysis depends more than just on the performance of the analytical method, which is typically quantified by metrics related to the rates of true and false results.
This interpretation also depends on the population from which the tested item was taken, quantified by the prevalence of the studied cases.
For instance, the probability of someone being infected with COVID, given the result of a positive test, does not depend solely on the probability of a real COVID case being correctly identified by the test; it also depends on the COVID prevalence in the population.
This leaflet shows how the interpretation of a qualitative result is affected by the prior information, using a (fictional!) example.
Availability
The second edition is currently available in English.
- Download the leaflet in English [598 kb] (2026-02-06)*
- Download the leaflet in German [336 kb] (2026-02-06)
* Dates are the date of addition to this website
Translation
Translation into other languages is encouraged for members of Eurachem. Other offers of translation should be directed to the Eurachem Secretariat for permission. The Eurachem policy on maintenance and development of Eurachem guidance, available on the Policies page, gives further information on translation.
The determination of clinical sensitivity and specificity of tests for binary disease detection is critical to ensure these tests are sufficiently reliable.
Validation of analytical methods (i.e. procedures) usually excludes the primary sampling, but this is now widely recognised as the first step in the measurement procedure. Validation of the whole measurement procedure therefore requires consideration of a performance characteristic that reflects the quality of all of the steps (including sampling and physical sample preparation). The uncertainty of the final measurement value is that key characteristic that unifies this whole measurement procedure and enables its validation, particularly when supported by performance characteristics that have an established role in the validation of an analytical procedure as a standalone activity.
