Results in the Constitution appear in the center column; results from essays appear in the right column. Use a short, descriptive search phrase. Precise phrases like âreligious freedom,â âtaxation,â or âwomenâs suffrageâ will work better than longer phrases.
Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related. We have perfect multicollinearity if, for example as in the equation above, the correlation between two independent variables is equal to 1 or -1.In practice, we rarely face perfect multicollinearity in a data set.rom Wikipedia, the free encyclopedia. In statistics, multicollinearity (also collinearity) is a 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 substantial degree of accuracy.
DEFINITION of 'Variance Inflation Factor'. A measure of the amount of multicollinearity in a set of multiple regression variables. The presence of multicollinearity within the set of independent variables can cause a number of problems in the understanding the significance of individual independent variables in the regression model. Using variance inflation factors helps to identify multicollinearity issues so that the model can be adjusted.