Speaker
Stephen Martin
(Northern Illinois University)
Description
The projected discovery and exclusion capabilities of searches are often quantified using the median expected $p$-value or its corresponding significance. However, this criterion can lead to flawed results, for example counterintuitively predicting lessened sensitivities if the experiment takes more data or reduces its background. We discuss the merits of several alternatives to the median expected significance, both when the background is known and when it is subject to some uncertainty. We advocate for standard use of the “exact Asimov significance” $Z^{\rm A}$ detailed in this talk.
Primary author
Stephen Martin
(Northern Illinois University)
