Multiple hypothesis testing for metrology applications

Scrutiny of hypotheses by means of statistical tests is a common practice in experimental research. However, valid inference drawn from data analysis needs scientific grounds, whereas conclusions based on significance tests or hypothesis testing may be problematic, especially when dealing with a multiplicity of tested hypotheses, as in experiments performed on bio-molecules. The problem of false discovery rate is focused in the present paper, aiming at eliciting application of sound criteria for rejection/acceptance of hypotheses, with a view of addressing related methods for uncertainty characterization.