Protski, Inc., an audit firm, wants to develop a multiple regression model that can explain the value of a house Y, measured in thousands of dollars, by the age of the house X₁, its square footage X₂, the number of bathrooms X₃, the absence

(0) or presence (1) of an attached garage D₁, and the absence (0) or presence (1)

of a view D₂. A random sample of 20 houses is used to gather observations.

Here are the results (standard errors are in parentheses):

The error sum of squares is 7,892; the total sum of squares is 9,665.

(a) Comment on the significance of the regression coefficients.

(b) Comment on the overall significance of this regression.

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= 63.53 .5827X, +.00956X2+.81X3 (38.12) (4907) (.01967) (11.75) -4.98D + 13.07D2 (19.01) (17.69)