# 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

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?

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?

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## a In the two independent variable case the coefficient of x 1 represents the expectâ€¦View the full answer

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**ISBN:** 9781305081598

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