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Basic Question 2 of 3
Multicollinearity in linear regression is caused by:
II. The dependent variable and an independent variable being highly correlated with each other.
III. Two or more dependent variables being highly correlated with each other.
IV. Two or more independent variables being highly correlated with each other.
I. Heteroskedastic and serially correlated residuals.
II. The dependent variable and an independent variable being highly correlated with each other.
III. Two or more dependent variables being highly correlated with each other.
IV. Two or more independent variables being highly correlated with each other.
User Contributed Comments 1
| User | Comment |
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| danlan2 | This is the definition |
I am using your study notes and I know of at least 5 other friends of mine who used it and passed the exam last Dec. Keep up your great work!
Barnes
Learning Outcome Statements
explain multicollinearity and how it affects regression analysis.
CFA® 2025 Level II Curriculum, Volume 1, Module 3.