Instrument calibration is an essential stage in most measurement procedures. It is a set of operations that establish the relationship between the output of the measurement system (e.g. the response of an instrument) and the accepted values of the calibration standards (e.g. the amount of analyte present). A large number of analytical methods require the calibration of an instrument.
As calibration is such a common and important step in analytical methods, it is essential that analysts have a good understanding of how to set up calibration experiments and how to evaluate the results obtained.
During August 2002 a benchmarking exercise was undertaken, which involved the preparation and analysis of calibration standards and a test sample using UV spectrophotometry. The aim of the exercise was to investigate the uncertainties associated with the construction of a calibration curve, and with using the calibration curve to determine the concentration of an unknown compound in an aqueous solution. In addition, it was hoped to identify any common problems encountered by analysts undertaking calibration experiments.
Members of the Environmental Measurement Training Network (EMTN) and the SOCSA Analytical Network Group (SANG) were invited to participate in the exercise. Five members of EMTN, six members of SANG and three organisations who are members of both EMTN and SANG submitted results. Some participants submitted results from more than one analyst, giving 19 sets of results in total.
The results of the benchmarking exercise were interesting. Although the exercise initially appeared relatively straightforward, a number of mistakes in carrying out the experiments and analysing the data were identified. Since a number of the mistakes occurred in more than one laboratory, it is likely that other laboratories carrying out similar exercises may make the same errors.
The aim of this guide is to highlight good practice in setting up calibration experiments, and to explain how the results should be evaluated. The guide focuses on calibration experiments where the relationship between response and concentration is expected to be linear, although many of the principles of good practice described can be applied to non-linear systems.
With software packages such as Excel, it easy to generate a large number of statistics. The guide also explains the meaning and correct interpretation of some of the statistical terms commonly associated with calibration.