Finally, I estimated Model 4, which uses the natural log of the price, ln(Price)

Question

Finally, I estimated Model 4, which uses the natural log of the price, ln(Price), for the response variable:

The regression equation is
lnPrice = 9.80 - 0.000008 Mileage + 0.105 Liter + 0.328 Cruise - 0.0550 Sound + 0.0531 Leather - 0.350 Cylinder_4
          - 0.418 Cylinder_6


Predictor          Coef     SE Coef      T      P
Constant         9.7957      0.1617 60.60 0.000
Mileage     -0.00000760 0.00000120 -6.34 0.000
Liter           0.10499     0.03140   3.34 0.001
Cruise          0.32772     0.02478 13.23 0.000
Sound          -0.05502     0.02172 -2.53 0.012
Leather         0.05306     0.02341   2.27 0.024
Cylinder_4     -0.34984     0.09961 -3.51 0.000
Cylinder_6     -0.41772     0.05714 -7.31 0.000

S = 0.277882   R-Sq = 54.5%   R-Sq(adj) = 54.1%

Suppose that the predicted ln(Price) for a car is [ln=9.3]. What is the predicted price for that car? Do not use the $ sign and give your answer with 3 decimal places.

Explanation / Answer

Given that the predicted ln(Price) for a car is [ln=9.3].

The predicted price for that car is exp(9.3) = 10938.019

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