In a regression model, if independent variables exhibit multicollinearity, then:
A) the strength of association of variables changes according to the beta coefficient.
B) determination of the best fitting line requires maximization of the vertical distances of all the points from the line.
C) standardization augments the effects of using different scales of measurement.
D) computing factor scores is the least effective approach to regression analysis.
E) the estimation of separate regression coefficients for the correlated variables becomes difficult.

Question

Quizplus · Accepted Answer

Multicollinearity makes it difficult to estimate separate regression coefficients for correlated variables because there will be ambiguity about the exact relationship between each independent variable and the dependent variable. This can make it challenging to accurately interpret the impact of each variable on the outcome, and could lead to potentially erroneous conclusions.

In a Regression Model, If Independent Variables Exhibit Multicollinearity, Then