The following estimated regression equation was developed for a model involving two independent variables. After x 2 was dropped from the model, the least squares method was used to obtain an estimated regression equation involving only x 1 as an independent variable. In the two independent variable case, the coefficient x 1 represents the expected change in Select corresponding to a one unit increase in Select when Select is held constant. In the single independent variable case, the coefficient x 1 represents the expected change in Select corresponding to a one unit increase in Select . Could multicollinearity explain why the coefficient of x 1 differs in the two models? Assume that x1 and x2 are correlated. Select