Speaker
Sergei Redin
(Budker Institute)
Description
In the presentation we consider systematic biases of fit parameters arising from a chi^2 minimization procedure, which we call "statistical biases of fit
parameters". We discuss several possible techniques, which may reduce those
statistical biases.
That may be extremely useful, in paticular for precision experiments with high statistics, if for technical reasons, for systematic studies, etc., the whole
data set has to be divided into many equal parts and then fit separately,
and the weighted average being used as a final result.
Some numerical estimates for the muon g-2 experiment are presented.
Author
Sergei Redin
(Budker Institute)
