Multicollinearity in a regression model occurs when:
Correct Answer
B) Two or more independent variables are highly correlated
Why this is correct: Multicollinearity occurs when two or more independent variables (predictors) in a regression model are highly correlated with each other (e.g., GLA and number of bedrooms). This makes it difficult to isolate the individual effect of each variable, leading to unstable coefficient estimates. Why the other choices are wrong: It is not caused by too few observations for the dependent variable. There is no rule that a model with more than five variables causes it. Randomly distributed residuals indicate a good model fit, not multicollinearity. Exam tip: If variables like bedrooms, bathrooms, and GLA all move together, watch for multicollinearity.
Why This Is the Correct Answer
Why this is correct: Multicollinearity occurs when two or more independent variables (predictors) in a regression model are highly correlated with each other (e.g., GLA and number of bedrooms). This makes it difficult to isolate the individual effect of each variable, leading to unstable coefficient estimates. Why the other choices are wrong: It is not caused by too few observations for the dependent variable. There is no rule that a model with more than five variables causes it. Randomly distributed residuals indicate a good model fit, not multicollinearity. Exam tip: If variables like bedrooms, bathrooms, and GLA all move together, watch for multicollinearity.
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