Proper linear model

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.

Bibliography

Dawes, R. M. (1979). "The robust beauty of improper linear models in decision making". American Psychologist. 34 (7): 571–582. doi:10.1037/0003-066X.34.7.571.

gollark: Planes can mostly autopilot themselves.

gollark: You just point the pointy end vaguely toward the horizon and press W and S to keep it there.

gollark: I've played Kerbal Space Program. It can't be that hard.

gollark: reddit users can *technically* speak English somewhat.

gollark: If the dataset consists of people who are able to spell and grammar somewhat, then the model should also do that.

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