Using Statistical Inference for Decision Making in Best Estimate Analyses

Abstract

For broad classes of safety analysis problems, one needs to make decisions when faced with randomly varying quantities which are also subject to errors. The means for doing this involves a statistical approach which takes into account the nature of the physical problems, and the statistical constraints they impose. We describe the methodology for doing this which has been developed at Nuclear Safety Solutions, and we draw some comparisons to other methods which are commonly used in Canada and internationally. Our methodology has the advantages of being robust and accurate and compares favourably to other best estimate methods.