John Howard, a Mobile Alabama, real estate developer, has revised a regression m

Question

John Howard, a Mobile Alabama, real estate developer, has revised a regression model to help determine residential housing prices in South Alabama. the model was developed using recent sales in a particular neighborhood. The price (Y) of the house is based on the size (square footage = X) of the house. the model is:
Y =13,473 + 37.65X
The coefficient correlation for the model is 0.63.

A) Use the model to predict the selling price of a house that is 1, 860 sqaure feet.
B) An 1,860-sqaure foot house recently sold for $95,000. Explain why this is not why the model predicted.
C. If you were going to use multiple regression to develop such a model, what other quantitative variables might you include?
D) What is the value of the coefficient of determination in this problem?

Explanation / Answer

A) selling price of a house = 13,473 + 37.65*1860=$83502

B) The price of the house is greater than predicted because model is only based on square footage and ignores other variables. Also the correlation coefficient is very low.

C. To use multiple regression, I would include other variables such as age of the house, number of bedrooms, number of appliaces, number of bathrooms, number of floors etc.

D. coefficient of determination is simply the squared value of the correlation

coefficient of determination =0.63^2 =0.3969

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