THE QUALITY OF STANDARDS IN LEAST SQUARES CALIBRATIONS

Frequently, the Least Square Regression Model (LSRM) assumption related to standards quality is either forgotten or formulated in too strict of a way, making its application unsuccessful or difficult. This work posits that the LSRM requires calibration standards with concentration ratios affected by negligible uncertainties that are achievable for standard solutions with large relative uncertainties. Criterion to test this assumption and a model to take into account the uncertainty of standards in performed quantifications are presented. The developed models were successfully tested with a combination of experimental data about interpolation uncertainty, for the determination of hexachlorobenzene by GC-ECD, with simulated values of standards concentrations.