4) Real estate investors, home buyers, and home owners often use the appraised value of a property as a basis for


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4) Real estate investors, home buyers, and home owners often use the appraised value of a property as a basis for predicting sale price. Data on sale prices and total appraised values of 92 residential properties sold in 1999 in an upscale Tampa, Florida neighborhood named Tampa Palms. The first five and last five observations of the data set are listed in the accompanying table.

Appraised Val.       Sale Price

170.432           180.0

212.827           245.1

68.130 85.4

65.505 87.9

68.655 84.2

64.980 85.0

67.605 81.0

100.861           125.0

108.981           124.0

102.523           126.0

104.203           128.5

102.681           127.5

105.175           128.2

80.954 107.0

101.515           125.0

89.119 116.0

102.066           122.5

89.588 118.9

106.118           120.0

147.865           188.0

158.260           183.0

161.309           195.5

162.395           193.0

151.475           192.0

203.826           256.9

222.012           270.0

214.728           230.0

259.848           332.5

217.125           310.0

220.041           230.5

228.806           257.0

253.876           300.0

205.529           275.0

318.508           365.0

202.127           258.0

263.847           279.0

286.744           340.0

324.578           335.0

266.542           297.0

140.743           166.0

151.305           187.0

148.115           163.4

182.272           59.0

170.863           221.0

270.040           290.0

235.087           260.0

348.574           445.0

302.133           406.0

136.315           185.0

116.446           176.0

133.912           171.1

153.250           182.0

127.930           166.5

306.172           295.0

298.680           369.0

289.489           350.0

315.663           365.0

320.017           390.0

348.574           365.0

352.985           440.3

112.242           100.3

225.613           220.0

150.348           187.0

169.282           214.0

171.832           185.0

156.224           182.5

144.384           165.0

139.940           167.0

127.706           160.0

111.856           130.9

125.731           160.0

128.329           142.8

615.586           560.0

572.523           715.0

140.040           176.0

164.849           178.0

125.187           156.5

149.202           153.0

422.913           528.0

372.377           475.0

330.554           427.0

929.396           957.5

192.105           260.0

201.886           262.0

159.705           154.0

223.001           260.0

179.056           215.0

195.862           244.0

176.850           219.0

95.718 132.0

137.108           156.9

183.704           263.0

  1. propose a straight-line model to relate the appraised property value x to the sale price y for residential properties in this neighborhood.b. a minitab scatterplot of the data is shown above.
    (note: both sale price and total appraised value are shown in thousands of dollars) Does it appear that a straight-line model will be an appropriate fit to the data?c. a minitab simple linear regression printout is also show above. Find the equation of the best fitting line through the data on the printout.

    d. interpret the y-intercept of the least squares line. Does it have a practical meaning for this application? Explain.

    e. interpret the slope of the least squares line. Over what range of x is the interpretation meaningful?

    f. use the least squares model to estimate the mean sale price of a property appraised at $300,000.

    MINITAB——————————————————————–
    The regression equation is
    SALEPRIC= 20.9 + 1.07 TotalVAl

    Predictor Coef SE Coef          T          P
    Constant                      20.942             6.446               3.25     0.002
    TotalVAl                     1.06873           0.02709           39.45   0.000

    S = 32.7865     R-Sq = 94.5%             R-Sq(adj) = 94.5%

    Analysis of Variance
    Source             DF                   SS                    MS      F              P
    Regression       1          1673142          1373142      1556.48      0.0

Residual Error 90        96746              1075

Total                91       1769888

Answer

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