DEVELOPMENT OF DATA SETS FOR THE VALIDATION OF ANALYTICAL INSTRUMENTATION

Analytical chemistry makes use of a wide range of basic statistical op erations, including means; standard deviations; significance tests bas ed on assumed distributions; and linear, polynomial, and multivariate regression. The effects of limited numerical precision, poor choice of algorithm, and extreme dynamic range on these common statistical oper ations are discussed. The effects of incorrect choice of algorithm on calculations of basic statistical parameters and calibration lines are illustrated by examples. Some approaches to validation of such softwa re are considered. The preparation of reference data sets for testing statistical software is discussed. The use of 'null space' methods for producing reference data sets is described, and an example is given. These data sets have well-characterized properties and can be used to test the accuracy of basic statistical procedures. Specific properties that are controlled include the numerical precision required to repre sent the sets exactly and the analytically correct answers. A further property of some of the data sets under development is the predictabil ity of the deviation from the expected results resulting from poor cho ice of algorithm.