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Title: Consumer Risk For Non-Gaussian Measurand Distributions
Author: Ricardo A. Nicholas
Source: 2002 Measurement Science Conference
Year Published: 2002
Abstract: A previous paper titled Measurement Decision Risk Simplified 1 dealt with Consumer and Producer Risk based on Normal probability densities for both the measurand and the measurement system. It treated each density as if the historical data was representative of a Normal random variable, which generally is not the case. For a finite sample size, assuming the population is Normally distributed and bilaterally symmetric about the mean, the historical data is best represented by a t density. Since, in real-world metrology, with its inherent finite sample sizes, it is not the Normal but the t density that must be the basis for the calculation of Consumer and Producer Risk. The main focus of this paper is to extend the approximation method of the previous paper to the treatment of real-world t and Uniform densities.

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