Abstract
The difference between the classical and the inverse least squares methods in the problem of calibrating an instrument is studied. We examine the probability that the ratio of the two estimates differs from unity by more than a specified small constant. The results show that this probability increases as the absolute value of the ratio of the regression slope and the standard deviation of the error decreases. Methods of estimating this probability are proposed. An example from the US pharmaceutical industry concerning potency assay is presented.
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