Exam 1

1. Metainformation

   Tag	Value
   file	Assumptions_vufgb-vif-008-en_vufgb-vif-008-en
   name	vufgb-vif-008-en
   section	Assumptions/Multicolinearity/VIF, Assumptions/Multicolinearity, Inferential Statistics/Regression/Multiple linear regression
   type	schoice
   solution	TRUE, FALSE, FALSE, FALSE
   Type	Conceptual, Calculation, Interpreting output
   Program
   Language	English
   Level	Statistical Thinking

   Question

   A researcher wants to know if there is extreme multicollinearity in her multiple linear regression with three predictors. The multiple correlation between $X_{1}$ and the other two predictors is 0.90. Calculate the VIF value for $X_{1}$.

   Based on this VIF value, is there extreme multicollinearity?

   
   
   1. TRUE: $VIF = 5.26$; though extreme multicollinearity
   2. FALSE: $VIF = 5.26$; no extreme multicollinearity
   3. FALSE: $VIF = 11.11$; no extreme multicollinearity
   4. FALSE: $VIF = 11.11$; though extreme multicollinearity
   
   

   Solution

   Use formula $VIF = \frac{1}{(1-R_{j}^{2})} = \frac{1}{(1-0.90^{2})} = \frac{1}{0.19} = 5.26$. A VIF value of 10 or higher is considered extreme multicollinearity. Values higher than 2-5 are otherwise considered “potentially problematic.

   
   
   1. Correct
   2. Incorrect
   3. Incorrect
   4. Incorrect