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Q. John Howard a mobile, Alabama, real estate developer, has devised a regression model to help decide residential housing prices in South Alabama. The model was developed using recent sales in a particular neighbourhood. 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 illustrated what the model predicted?
c) If you were going to use multiple regressions to develop such a model, illustrate what other quantities variables might you comprise?
d) Illustrate what is the value of the coefficient of determination in this problem?
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