1. What is the formula for VIF?
2. What is a common source of multicollinearity?
3. Auxiliary regression means
4. What does a high R² but insignificant t-ratios indicate?
5. What happens if you include all categories of dummy variables?
7. When a variable is highly correlated with others, it becomes:
8. Which of the following is NOT the cause of multicollinearity
9. Perfect multicollinearity means
10. What is the inverse of VIF?
11. A VIF Value close to 1 indicates
12. What is one remedy for multicollinearity?
13. What does a large Variance Inflation Factor (VIF) indicate?
15. Which of the following techniques help detect multicollinearity?
16. What does the presence of common trends in variables lead to?
17. In the presence of imperfect multicollinearity, OLS estimators are:
18. What is the consequence of multicollinearity on confidence intervals?
19. What does increasing sample size help with?
20. What is a good threshold for VIF indicating possible multicollinearity?
21. What happens to t-ratios due to multicollinearity?
22. What is the consequence of perfect multicollinearity?
23. What does tolerance near zero indicate?
24. What happens to standard errors in presence of multicollinearity?
25. What happens in exact micronumerosity?
26. What does Eigenvalue condition number above 1000 indicate?
27. VIF for a variable is calculated as:
28. What is the main issue with dummy variable trap?
29. Which VIF value suggests severe multicollinearity?
31. In the presence of perfect multicollinearity standard errors become
32. What type of regression can handle multicollinearity?
33. What is the main problem caused by multicollinearity in interpretation?
34. What does a scatterplot close to a line indicate?
36. What does the F-test in auxiliary regression help detect?
37. Multicollinearity is a problem because it:
38. High pairwise correlation between independent variables is a sign of
39. What does the Klein rule of thumb suggest?
40. One way to address multicollinearity is to:
41. What is the main goal of regularization methods like Lasso?
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