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Over the past few years linear regression taking into account the errors in both axes has become increasingly important in chemical analysis. It can be applied for instance in method comparison studies at several levels of concentration (where each of the two methods normally present errors of the same order of magnitude) or at calibration straight lines using reference materials as calibration standards,...
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