Computer simulation of the uncertainty of analytical results

Uncertainty is an important quality parameter of any analytical result. Estimating the uncertainty of analytical procedures can be rather difficult in many instances. Computer simulation based on multiple repetition of calculation of the resulting quantity while varying slightly the input parameters is an alternative option. The input parameters for the various computation runs are composed of two terms: the constant mean value and the error, obtained as the product of the standard uncertainty of the parameter in question and a random number with the normal distribution N(0.1). This approach can also serve to optimize measuring procedures, as demonstrated on an example of the determination of lead in biological materials by isotope dilution mass spectrometry. The accuracy of the optimized method was tested by analysis of some CRMs, the robustness of the method was examined, and the detection limit (10 ng/g Pb) and repeatability (4 ng/g Pb) were determined.