Quantifying Uncertainty of Determination by Standard Additions and Serial Dilutions Methods Taking into Account Standard Uncertainties in Both Axes

Abstract

The analytical expressions for the calculation of the standard uncertainty of the predictor variable either extrapolated or interpolated from a calibration line that takes into account uncertainties in both axes have been derived and successfully verified using the Monte Carlo modeling. These expressions are essential additions to the process of the analyte quantification realized with either the method of standard additions (SAM) or the method of serial dilutions (MSD). The latter one has been proposed as an alternative approach to the SAM procedure. In the MSD approach instead of the sequence of standard additions, the sequence of solvent additions to the spiked sample is performed. The comparison of the calculation results based on the expressions derived to their equivalents obtained from the Monte Carlo simulation, applied to real experimental data sets, confirmed that these expressions are valid in real analytical practice. The estimation of the standard uncertainty of the analyte concentration, quantified via either SAM or MSD or simply a calibration curve, is of great importance for the construction of the uncertainty budget of an analytical procedure. The correct estimation of the standard uncertainty of the analyte concentration is a key issue in the quality assurance in the instrumental analysis.