The following estimated regression equation was developed for a model involving two independent variables.
y = 40.7 + 8.63x1 + 2.71x2
After x2 was dropped from the model, the least squares method was used to obtain an estimated regression equation involving only x1 as an independent variable.
y = 42.0 + 9.01x1
a. Give an interpretation of the coefficient of x1 in both models.
b. Could multicollinearity explain why the coefficient of x1 differs in the two models? If so, how?