Systematic errors in analytical measurement results

Abstract

Definitions of the concepts of bias and recovery are discussed and approaches to dealing with them described. The Guide To Uncertainty in Measurement (GUM) recommends correction for all significant systematic effects, but it is also possible to expand measurement uncertainty to take account of uncorrected bias. Run, laboratory and method bias can be defined as components of the bias of a particular measurement result, and can be useful as concepts used in method validation. Estimation of run bias allows a simplification of the estimation of measurement uncertainty. Multivariate calibration brings its own biases that must be quantified and minimised.