Premium
Sixteen Statistical Tests for Outlier Detection and Rejection in Evaluation of International Geochemical Reference Materials: Example of Microgabbro PM‐S
Author(s) -
Verma Surendra P.
Publication year - 1997
Publication title -
geostandards newsletter
Language(s) - English
Resource type - Journals
eISSN - 1751-908X
pISSN - 0150-5505
DOI - 10.1111/j.1751-908x.1997.tb00532.x
Subject(s) - outlier , univariate , statistics , anomaly detection , standard deviation , sample (material) , confidence interval , mathematics , sample size determination , data mining , computer science , multivariate statistics , chemistry , chromatography
A totally objective procedure involving sixteen statistical tests (a total of thirty four single or multiple outlier versions of these tests) for outlier detection and rejection in a univariate sample is applied to a data base of sixty four elements in a recently issued international geochemical reference material (RM), a microgabbro PM‐S from Scotland. This example illustrates the relative importance and usefulness of these tests in processing modern geochemical data for possible outliers and obtaining mean concentration and other statistical parameters from a final normal sample of univariate data. The final mean values are more reliable (characterized by smaller standard deviations and narrower confidence limits) than those obtained earlier using an accommodation approach (robust techniques) applied to this data base. Very high quality (certified value equivalent, cve) mean data are now obtained for eleven elements as well as high quality recommended values (rv) for thirty three elements in PM‐S. Earlier work using the accommodation approach failed to establish even one cve value for any of the sixty four elements compiled here. The present procedure of outlier detection and elimination is therefore recommended in the study of RMs