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The Following Regression Model Has Been Proposed to Predict Sales

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The following regression model has been proposed to predict sales at a furniture store. The following regression model has been proposed to predict sales at a furniture store.   = 10 - 4x<sub>1</sub> + 7x<sub>2</sub> + 18x<sub>3</sub> where x<sub>1</sub> = competitor's previous day's sales (in $1,000s) x<sub>2</sub> = population within 1 mile (in 1000s) x<sub>3</sub> = 1 if any form of advertising was used, 0 if otherwise   = sales (in $1,000s)  a.Fully interpret the meaning of the coefficient of x<sub>3</sub>. 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. = 10 - 4x1 + 7x2 + 18x3
where
x1 = competitor's previous day's sales (in $1,000s)
x2 = population within 1 mile (in 1000s)
x3 = 1 if any form of advertising was used, 0 if otherwise The following regression model has been proposed to predict sales at a furniture store.   = 10 - 4x<sub>1</sub> + 7x<sub>2</sub> + 18x<sub>3</sub> where x<sub>1</sub> = competitor's previous day's sales (in $1,000s) x<sub>2</sub> = population within 1 mile (in 1000s) x<sub>3</sub> = 1 if any form of advertising was used, 0 if otherwise   = sales (in $1,000s)  a.Fully interpret the meaning of the coefficient of x<sub>3</sub>. 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. = 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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