Assertion: regression's variable | /r/HasProperty | correlated with each other
Facets:
value: highly
type: DEGREE
Source sentences:
text: If the independent variables are highly correlated with each other, it will be difficult to assess the true relationships between the dependent and independent variables.
text: However, you do not need to check if the explanatory variables are correlated with each other.
text: Because they are mutually uncorrelated, using principal components solves the problem of multicollinearity (explanatory variables that are correlated with each other) in the regression model.
text: Assumption #6: Your data must not show multicollinearity , which occurs when you have two or more independent variables that are highly correlated with each other.
text: Your data must not show , which occurs when you have two or more independent variables that are highly correlated with each other.