Abstract
In this work a simple and convenient model is proposed for studying features of the multicollinearity effect in regression analysis. Using some reasonable approximations a multivariate regression is reduced to a kind of bivariate regression by each predictor. This approach yields some criteria for identifying the cases of evident multicollinearity, and leads to a better understanding of properties of multiple regression.
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