Proper linear model

From HandWiki
Revision as of 22:49, 6 February 2024 by John Stpola (talk | contribs) (fix)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

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.