Tests of goodness of fit to multiple data sets
arXiv:hep-ph/0105207
Abstract
We propose a new and rather stringent criterion for testing the goodness of fit between a theory and experiment. It is motivated by the paradox that the criterion on χ^2 for testing a theory is much weaker than the criterion for finding the best fit value of a parameter in the theory. We present a method by which the stronger parameter-fitting criterion can be applied to subsets of data in a global fit.
22 pages, 8 figures