Home prices Many variables have an impact on deter-mining the price of a house. A few of these are Size of the house (square feet), Lotsize, and number of Bathrooms.Information for a random sample of homes for sale inthe Statesboro, Georgia, area was obtained from theInternet. Regression output modeling the Asking Pricewith Square Footage and number of Bathrooms gave thefollowing result:Dependent Variable is Asking Prices = 67013 R-Sq = 71.1, R-Sq (adj) = 64.6,Predictor Coeff SE(Coeff) t-Ratio P-ValueIntercept -152037 85619 -1.78 0.110Baths 9530 40826 0.23 0.821Sq ft 139.87 46.67 3.00 0.015Analysis of VarianceSource DF SS MS F-Ratio P-ValueRegression 2 99303550067 49651775033 11.06 0.004Residual 9 40416679100 4490742122Total 11 1.39720E+11a) Write the regression equation.b) How much of the variation in home asking prices isaccounted for by the model?c) Explain in context what the coefficient of SquareFootage means.d) The owner of a construction firm, upon seeing this model, objects because the model says that the num-ber of bathrooms has no effect on the price of the home. He says that when he adds another bathroom, it increases the value. Is it true that the number of bath-rooms is unrelated to house price? (Hint: Do you think bigger houses have more bathrooms?)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Home prices Many variables have an impact on deter-
mining the price of a house. A few of these are Size of the

house (square feet), Lotsize, and number of Bathrooms.
Information for a random sample of homes for sale in
the Statesboro, Georgia, area was obtained from the
Internet. Regression output modeling the Asking Price
with Square Footage and number of Bathrooms gave the
following result:
Dependent Variable is Asking Price
s = 67013 R-Sq = 71.1, R-Sq (adj) = 64.6,
Predictor Coeff SE(Coeff) t-Ratio P-Value
Intercept -152037 85619 -1.78 0.110
Baths 9530 40826 0.23 0.821
Sq ft 139.87 46.67 3.00 0.015
Analysis of Variance
Source DF SS MS F-Ratio P-Value
Regression 2 99303550067 49651775033 11.06 0.004
Residual 9 40416679100 4490742122
Total 11 1.39720E+11
a) Write the regression equation.
b) How much of the variation in home asking prices is
accounted for by the model?
c) Explain in context what the coefficient of Square
Footage means.
d) The owner of a construction firm, upon seeing this

model, objects because the model says that the num-
ber of bathrooms has no effect on the price of the

home. He says that when he adds another bathroom, it

increases the value. Is it true that the number of bath-
rooms is unrelated to house price? (Hint: Do you think

bigger houses have more bathrooms?)

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