Factor transformation to produce statistics describing the uncertainty of analytical data

Analytical uncertainty produced by random error has a positively skewed distribution and accuracy and precision have non-linear scales. Compared with conventional statistics, factor transformation of the data allows more appropriate interpretation of results and facilitates graphical inspection of data. Statistics are compared for practical examples of performance in proficiency tests and of repeatability and reproducibility in collaborative studies. Factor transformation is shown to be applicable to wide ranges of analyte concentration and measurement precision.