Assessment of measurement uncertainty using Monte Carlo method based on STATISTICA

In the paper the assessment of measurement uncertainty using Monte Carlo method based on STATISTICA PL is presented. In particular the problem of choice of the distribution of the input quantity is described. A comparative analysis results of the assessment method of measurement uncertainty associated with the uncertainty propagation law and the Monte Carlo simulation method is presented. In the case of Monte Carlo method the choice of the distribution of input quantities is an important element because, on this basis a new random sample is generated. The estimation quality of population parameters has an influence on result of the uncertainty assessment based on this method. Particular care should be taken during the uncertainty assessment of measurement encumbered with a significiant uncertainty. The limitations of Monte Carlo method are described. It was found that the basic method for the uncertainty assessment of measurement should be the method based on GUM using the uncertainty propagation law. (Assessment of measurement uncertainty using Monte Carlo method based on STATISTICA).