Abstract
We consider the paradoxical situation arising in the standard multiple regression analysis in that as the standard error of prediction decreases by introduction of additional variables (descriptors) at the same time the standard error of the coefficients of the regression analysis increases, often to the point of the coefficients having no statistical validity. We trace the origin of this paradoxical situation to intercorrelation of the variables. A remedy to this curve-fitting paradox is in the introduction of orthogonal variables or descriptors. © 1994 John Wiley & Sons, Inc.
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