General Studies · Multicollinearity in Regression
In a multiple linear regression model, the presence of multicollinearity typically leads to high standard errors and would result in:
Verified Solution4 OptionsUpdated: October 2026👁️1 View
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- 1Low variance of regression coefficients
- 2A sharp increase in the 't' value for one variable when another collinear variable is dropped from the model✓
- 3Inability to estimate regression parameters completely
- 4Low standard errors for parameter estimates
Correct answer
A sharp increase in the 't' value for one variable when another collinear variable is dropped from the model
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