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- Multicollinearity abstract "Multicollinearity is a statistical phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a non-trivial degree of accuracy. In this situation the coefficient estimates of the multiple regression may change erratically in response to small changes in the model or the data. Multicollinearity does not reduce the predictive power or reliability of the model as a whole, at least within the sample data themselves; it only affects calculations regarding individual predictors. That is, a multiple regression model with correlated predictors can indicate how well the entire bundle of predictors predicts the outcome variable, but it may not give valid results about any individual predictor, or about which predictors are redundant with respect to others.A high degree of multicollinearity can also prevent computer software packages from performing the matrix inversion required for computing the regression coefficients, or it may make the results of that inversion inaccurate.Note that in statements of the assumptions underlying regression analyses such as ordinary least squares, the phrase "no multicollinearity" is sometimes used to mean the absence of perfect multicollinearity, which is an exact (non-stochastic) linear relation among the regressors.".
- Multicollinearity wikiPageExternalLink m.html.
- Multicollinearity wikiPageID "1486691".
- Multicollinearity wikiPageRevisionID "602238304".
- Multicollinearity hasPhotoCollection Multicollinearity.
- Multicollinearity id "9.0".
- Multicollinearity title "Econometrics Lecture".
- Multicollinearity subject Category:Regression_analysis.
- Multicollinearity comment "Multicollinearity is a statistical phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a non-trivial degree of accuracy. In this situation the coefficient estimates of the multiple regression may change erratically in response to small changes in the model or the data.".
- Multicollinearity label "Multicolinealidad".
- Multicollinearity label "Multicolinearidade".
- Multicollinearity label "Multicollineariteit".
- Multicollinearity label "Multicollinearity".
- Multicollinearity label "Multikollinearität".
- Multicollinearity label "Мультиколлинеарность".
- Multicollinearity label "多重共线性".
- Multicollinearity sameAs Multikolinearita.
- Multicollinearity sameAs Multikollinearität.
- Multicollinearity sameAs Multicolinealidad.
- Multicollinearity sameAs Multikolinearitas.
- Multicollinearity sameAs 다중공선성.
- Multicollinearity sameAs Multicollineariteit.
- Multicollinearity sameAs Multicolinearidade.
- Multicollinearity sameAs m.0557vl.
- Multicollinearity sameAs Q1332350.
- Multicollinearity sameAs Q1332350.
- Multicollinearity wasDerivedFrom Multicollinearity?oldid=602238304.
- Multicollinearity isPrimaryTopicOf Multicollinearity.