On normal and log-normal models imposed on results from proficiency tests for genetically modified organisms (GMO).

Abstract

This work forms a background to the recent discussion about normal and log-normal distributions in the results of proficiency tests for GMO analysis. In order to clear up some common confusions, the paper first covers some basic principles, viz., a comparison of normally and log-normally distributed samples of results at various precisions, and a background to the determination of assigned values and scoring in proficiency tests. Then follows brief discussions on the identification of outliers and the use of 'tests for normality'. In conclusion, there is a broad outline of the steps that may assist a proficiency testing scheme in deciding on a suitable model of dispersion.