Model to predict the selling price of a house


John Howard, a Mobile, Alabama, real estate developer, has devised 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 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) An 1,860-square-foot house recently sold for $95,000. Explain why this is not what 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?

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Business Management: Model to predict the selling price of a house
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