Steve Caples, a real estate appraiser in Lake Charles, Louisiana, has developed

Question

Steve Caples, a real estate appraiser in Lake Charles, Louisiana, has developed a regression model to hep appraise residental housing in the Lake Charles area. The model was developed using recently sold homes in a particular neighborhood. The price (Y) of the house is based on the square footage (X) of the house, The model is Y hat =33,478 + 62.4X. The coefficient of correlation for the model is 0.63.   (a) Use the model to predict the selling price of a house that is 1,860 square feet.    (b) A house with 1,860 square feet recently sold for $165,000. Explain why this is not what the predicted.   (c) If you were going to use multiple regression to develop an appraisal model, what other quantitative variables might be included in the model?   (d) What is the coefficient of determination for the model?

Explanation / Answer

a) predicted selling price of a house that is 1,860 square feet

=33478+(62.4*1860)=149542

b) Since the correlation coefficient is 0.63, so there is not exactly a perfect linear relationship between x and y, so the actualy selling price can be expected to quite deviate from the predicted.

d) the coefficient of determination for the model=0.632=0.3969

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