If multicollinearity is present, one solution is to A) add at least one more independent variable to the equation B) remove one of the very strongly correlated independent variables from the equation C) switch to a nominal dependent variable D) use the values of the unstandardized and standardized coefficients but not use the values for R and R²

Question

Quizplus · Accepted Answer

When multicollinearity is present, it means that there is a high correlation among the independent variables. This can cause problems in the model as the coefficients may become unstable or difficult to interpret. The best solution in this situation is to remove one of the strongly correlated independent variables from the equation. This can help to reduce the multicollinearity and improve the stability and interpretability of the model. Adding another independent variable may not solve the problem and may actually exacerbate it. Switching to a nominal dependent variable or only using the unstandardized and standardized coefficients but not R and R² will not address the issue of multicollinearity.

If Multicollinearity Is Present, One Solution Is to