SIPVADE: A new computer programme with seventeen statistical tests for outlier detection in evaluation of international geochemical reference materials and its application to Whin Sill Dolerite WS-E from England and Soil-5 from Peru

A new computer programme was written in programming language TURBOC, which enables us to apply a procedure involving seventeen statistical tests (a to tal of sixty five single or multiple outlier versions of these tests) for o utlier detection in univariate sample at a high confidence level of 99% (si gnificance level alpha = 0.01). The outlying observations should be evaluat ed first for technical reasons and then rejected manually from the data bas e until no more outliers are detected and the final statistical parameters are computed from the remaining data. This programme has been used successf ully to process two reference material data bases: WS-E from England and So il-5 from Peru. The final mean values for WS-E are more reliable (character ized by smaller standard deviations and narrower confidence limits) than th ose obtained earlier using a different statistical approach. The applicatio n of a large number of statistical tests to Soil-5 also resulted in smaller standard deviation values for most elements than the method involving a li mited number of such tests. For WS-E, some laboratories seem to have produc ed multiple data that were detected as statistical outliers. A close analys is of the distribution of outliers as a function of laboratory, country and analytical method leads to a technical justification for these outlying ob servations, probably in terms of inadequate QA/QC practices. Use of geochem ical criteria indicates that the new mean values in WS-E might be closer to the "true" concentrations. This procedure of outlier detection and elimina tion is therefore recommended in the study of the existing RM.