Question

Exercise 14-35 Algo A realtor in Arington, Messschusetts, 1; 5no yzing the restionanla betw een tne saie price of 5 home Price In SI, ts "uner footage Gqft. tne number oroecrooms secsl, and tne number of oothrooms etnsl. Sne colects ast2 on 36 gsies 1n Arlington in the first quarter of 2009 for the analyss. A partionof the data s shown In the accompanying teble. 58,7 2,381.8 1 1.8 a. Estim te tne model Price . ·ySqt-o ,Bed; +63Bstn; . E. (Round Coefficients to 2 decimal places.) de Intarcopt b-1. Interpret the coefficent of sqft For every addtional aquare foot the predicted price ofa hame Incresse by $15.34 For every square foot the predicted price of s hame Incresses by $115.34, holding number of bedrooma and bsthrooms constant For every addtional aquare foot the predicted price ofa hame Incresse by $115.34, holding aquare foot, number of bedrooms and bsthrooms constant b-2 Interpret the coefficlent of beda For every addtional bedroom, the predicted price ofa home Incressea by $39,099.91. o For every ย dtional bearoom, the predictea price of 5 home increases by $39,089.91, holding square footage end number of For every addtional bedroom, the predicted price ofa hame Incressea by $38,099.91, halaing aquare foot, number of b-3.Interpret the coefficlent of bstha For every addtional bathroom, the predicted price of s hame Incresse by $51,86214 o For every ย ditional bathroom. the predicted price of 5 home lncreese"y S51.86214. noding square footege and number of bedrooma constant o For every·dditional bathroom. the predicted price of 5 homelncreese"y S51.86214. noding square foot, number of c. Predict tne price of 5 2112 squar foot nome with two bedrooms and one oethrooms. Round coefficient estimates to at leas declmal places and final answer to the nearest whoe number) 1Price 2| 672000| 2214 3 758769 2308 4 831833 2800 5 689000 2200 6 685000 2716 7 645000 2524 8 625000 2732 9 620000 2436 10 7833332800 SftBeds Baths 2.0 3.0 2.5 3.5 2.0 2.5 3.5 2.0 0 11 585000 1947 12 583000 2224 13 3793332175 14 546000 792 15 780000 2149 16 732273 3964 17 344000 1301 1851 10001 1752 19 714000 2418 20 693000 2369 21 648200 2400 22 639800 2310 23 451000 1685 24 628333 2167 2.5 2.0 2.5 3.5 3.0 3.0 3.0 3.0 2.0 2.5 1.5 25 431700 1896 26 414000 1182 27 602250 728 2.0 2.0 2.0 2.0 28 478800 1660 29 3800001344 30 475000 1590 31 375900 2275 32 372000 1005 33 459375 1590 34 356500 1431 35 412500 1703 36 412500 1831 37 307500850 2.0 2.0 2.0 2.0

Answer 1

EXCEL Mega Stat) output Regression Analysis R2 0.661 Adjusted R 0.630 R 0.813 Dep. Var. Price Std. Error 90251.192 ANOVA table Source df 3 169,673,576,677.1600 20.83 .14E-07 MS Regression 509,020,730,031.4800 Residual 260,648,887, 422.8250 32 8,14 35 .277,731.9633 Total 769,669,617,454.3050 confidence interval ssion out variables Intercept Sqft Beds Baths coefficients std error 83,293.1406 65,950.5391 115.3420 39.1422 38,089.9056 22,006.1069 51,862.1447 26,951.8232 t(df-32)-p-value--.95% lower 95% upper ..std coeff 0.000 95.0721 0.467 0.223 0.261 1.263 2157 -51,043.7110 217,629.9921 2.947 0059 35.6119 1.731 0931 -6,735.0672 82,914.8783 1.924 0633 -3,036.9224 106,761.2119 Coefficients 83293.14 115.34 38089.91 51862.14 Intercept Saft Beds Baths

(b-1) For every additional square foot, the predicted price of a home increases by S115.34, holding number of bedrooms and bathrooms constant (b-2) For every additional bedroom, the predicted price of a home increases by S38089.91, holding square footage and number of baths constant (b-3) For every additional bathroom, the predicted price of a home increases by S51862.14, holding square footage and number of bedrooms constant Pricê 111867.95+110.94 Sqft +32809.38Beds +49441.77 Baths -111867.95+110.94(2112)+32809.38 (2) +49441.77(1) Pricê $461234