A Realtor in Arlington, Massachusetts, is analyzing the relationship between the sale price of a home (Price in \$), its square footage (Sqft), the number of bedrooms (Beds), the number of bathrooms (Baths), and a Colonial dummy variable (Colonial equals 1 if a coloni style home, 0 otherwise). She collects data on 36 sales in Arlington for the analysis. A portion of the data is shown in the accompanying table. Click here for the Excel Data File a. Estimate the model Price =b0+b1Sqft+2 Beds +b3 Baths +b4 Colonial +. (Negative values should be indicated by a minus sign Round Coefficients to 2 decimal places.) b-1. Interpret the coefficient of beds. For each additional bedroom in a house, the average price of a house is expected to decrease by $17,798, all else constant. For each additional bedroom in a house, the average price of a house is expected to increase by $17,798, all else constant. As the price of a house decreases by $17,798, the house is expected to have one more bedroom, all else constant. As the price of a house decreases by $17,798, the house is expected to have one less bedroom, all else constant. b-2. Interpret the coefficient of colonial. All else constant, the price of a colonial-style house is, on average, \$57,109 more than a non-Colonial style. All else constant, the price of a colonial-style house is, on average, \$57,109 less than a non-Colonial style. All else constant, the price of a colonial-style house is, on average, $183,859 more than a non-Colonial style. All else constant, the price of a colonial-style house is, on average, $183,859 less than a non-Colonial style house. c. Predict the price of a 2,500 square-foot, colonial-style home with three bedrooms and two bathrooms. (Do not round intermediate calculations. Round final answer to the nearest whole number.) \begin{tabular}{|c|c|c|c|c|} \hline Price & Sqft & Beds & Baths & Colonial \\ \hline 880000 & 2538 & 4 & 2.5 & 1 \\ \hline 809000 & 2257 & 1 & 1.5 & 1 \\ \hline 700000 & 2343 & 2 & 3.0 & 1 \\ \hline 691000 & 2042 & 2 & 2.5 & 1 \\ \hline 720000 & 2496 & 1 & 3.5 & 0 \\ \hline 639000 & 2447 & 3 & 2.5 & 0 \\ \hline 642000 & 2749 & 1 & 2.5 & 0 \\ \hline 620000 & 2213 & 2 & 3.5 & 0 \\ \hline 557000 & 2224 & 4 & 1.5 & 0 \\ \hline 621000 & 2139 & 2 & 1.5 & 0 \\ \hline 585000 & 2403 & 4 & 3.5 & 0 \\ \hline 530000 & 3018 & 1 & 1.0 & 0 \\ \hline 583000 & 1982 & 1 & 3.0 & 1 \\ \hline 531000 & 1443 & 2 & 1.5 & 0 \\ \hline 586000 & 2855 & 3 & 3.5 & 1 \\ \hline 468000 & 2035 & 2 & 1.0 & 0 \\ \hline 529000 & 1992 & 1 & 1.5 & 0 \\ \hline 552000 & 1953 & 2 & 3.0 & 1 \\ \hline 504000 & 1860 & 3 & 2.0 & 0 \\ \hline 507000 & 1861 & 3 & 2.0 & 0 \\ \hline 484000 & 1671 & 2 & 3.0 & 1 \\ \hline 459000 & 1535 & 1 & 3.0 & 0 \\ \hline 422000 & 1359 & 4 & 1.5 & 1 \\ \hline 413000 & 1978 & 4 & 1.5 & 1 \\ \hline 458000 & 963 & 3 & 1.5 & 1 \\ \hline 430000 & 1032 & 1 & 2.0 & 1 \\ \hline 353000 & 1291 & 2 & 2.0 & 0 \\ \hline 361000 & 1172 & 4 & 1.0 & 0 \\ \hline 390000 & 1513 & 2 & 1.0 & 0 \\ \hline 406000 & 2365 & 2 & 1.0 & 1 \\ \hline 346000 & 879 & 4 & 1.0 & 1 \\ \hline 386000 & 1458 & 4 & 2.0 & 1 \\ \hline 342000 & 1632 & 4 & 3.0 & 0 \\ \hline 312000 & 1419 & 3 & 2.0 & 0 \\ \hline 311000 & 1364 & 3 & 1.0 & 0 \\ \hline 300000 & 786 & 3 & 1.0 & 0 \\ \hline \end{tabular}