In statistics, a proper linear model is a linear regression model in which the weights given to the predictor variables are chosen in such a way as to optimize the relationship between the prediction and the criterion.
Simple regression analysis is the most common example of a proper linear model.
Unit-weighted regression is the most common example of an improper linear model.
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