Testing of data evaluation methods

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Abstract

When determining the recommended value for a physical quantity, the evaluator is sometimes faced with the problem of how best to derive such a value. A literature search often yields discrepant values from different experiments or laboratories. In the present work a number of data evaluation procedures proposed in the last two decades have been tested on randomly generated data sets with different types of outliers. A modified Bayesian procedure is shown to be the most reliable, and this method has been applied to half-life data to give the following values: 137Cs = 10985±12 d, 90Sr = 10544±20 d, 154Eu = 3138.5±0.3 d and 252Cf = 968.0±0.8 d.

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