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The Following Regression Model Has Been Proposed to Predict Sales Y^\hat { Y }

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The following regression model has been proposed to predict sales at a furniture store.
Y^\hat { Y } = 10 - 4X1+7X2+18X3
where
X1 = competitor's previous day's sales in $1,000s) X2 = population within 1 mile in 1,000s)
X3 = 1 if any form of advertising was used, 0 if otherwise
Y^\hat { Y } = sales in $1,000s)
a. Fully interpret the meaning of the coefficient of X3.
b. Predict sales in dollars) for a store with competitor's previous day's sale of $3,000, a population of 10,000 within 1 mile, and six radio advertisements.


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