Calibration allows the user to relate instrumental measurements to the sample of interest. Multivariate calibration allows for the analysis of several measurements from several samples or specimens. The method contributes to the two steps procedure where step one involves the calibration of data and second step involves the prediction that are made or based on the calibration. In calibration, indirect measurements are made from samples where the amount of the analyte has been predetermined, usually by an independent assay or technique. These measurements, along with the predetermined analyte levels, comprise a group known as the calibration set. This set is used to develop a model that relates the amount of sample to the measurements by the instrument. In some cases, the construction of the model is simple due to a certain relationship, such as Beer`s Law in the application of UV spectroscopy. Unlike spectroscopy, other cases can be much more complex, and it is in these cases where construction of the model is time-consuming step. Once the model is constructed, it can predict analyte levels based on measurements of new samples. It can be used to separate samples from interferences without the need of highly selective measurements for the analyte. Calibration techniques (used in the calibration step) differ in determining coefficient values for the preceding or similar equations.
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