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Tests of goodness of fit to multiple data sets

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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 \chi^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.

fields

hep-ph 1

years

2019 1

verdicts

UNVERDICTED 1

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