The output below is from a multiple linear regression analysis done by an area realty group. The analysis is intended to link y, the time that a house listed for sale remains on the market, to the size of the house (x₁), the listing price (x₂), and the age of the house (x₃).

a. Identify and interpret the estimated regression coefficients for x1, x2, and x3. 

b. Fill in the values of Multiple R and R Square. 

c. Show that the standard error of estimate that appears in row 4 of the Regression Statistics section of the table is equal to the square root of SSE/(n – k – 1), where n = number of observations and k = number of independent variables.

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Regression Statistics Multiple R R Square Adjusted RSq Standard Error Observations b) 0.74 23.59 21 ANOVA Regression Error (Residual) Total 2 33309.47 9459.19 42768.67 Intercept size (ft price (5000s) age years) Coeffs -35.770 0027 0.036 2.668