Discussion
The VIF measures :
Answer: C
The VIF measures multicollinearity.
The variance inflation factor of a predictor is \(1/(1 - R_j^{2})\), where \(R_j^{2}\) comes from regressing that predictor on all the others. It shows how much the variance of its regression coefficient is inflated by its overlap with the other predictors. A VIF of 1 means no overlap; values above about 4 or 5 are usually taken as a warning, so SPM's VIF of 4.2 signals that it is strongly correlated with the other predictors, probably CCFT.
The proportion of variance explained is \(R^{2}\). Heteroscedasticity is unequal spread of the residuals, checked with residual plots or tests such as Breusch-Pagan. The residual standard error is the typical size of a residual. None of these is what VIF measures.
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