where y = Bo + B₁x₁ + ₂x₂ + 3x3 + E X₁ = number of competitors within one mile X₂ = population within one mile (1,000s) 1 if drive-up window present 0 otherwise y = sales ($1,000s). The following estimated regression equation was developed after 20 outlets were surveyed. ŷ = 10.9 - 4.2x₁ + 6.8x₂ + 15.9x3 (a) What is the expected amount of sales (in dollars) attributable to the drive-up window? $ 15900 X3 =
where y = Bo + B₁x₁ + ₂x₂ + 3x3 + E X₁ = number of competitors within one mile X₂ = population within one mile (1,000s) 1 if drive-up window present 0 otherwise y = sales ($1,000s). The following estimated regression equation was developed after 20 outlets were surveyed. ŷ = 10.9 - 4.2x₁ + 6.8x₂ + 15.9x3 (a) What is the expected amount of sales (in dollars) attributable to the drive-up window? $ 15900 X3 =
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Transcribed Image Text:Management proposed the following regression model to predict sales at a fast-food outlet.
y = ß0 + B₁×₁ + B₂×₂ + B3×3 + ε
where
X1
x2
1 if drive-up window present
0 otherwise
y = sales ($1,000s).
The following estimated regression equation was developed after 20 outlets were surveyed.
10.9 4.2x₁ + 6.8x₂ + 15.9x3
x3
=
ŷ =
$
number of competitors within one mile
population within one mile (1,000s)
=
(a) What is the expected amount of sales (in dollars) attributable to the drive-up window?
$ 15900
(b) Predict sales (in dollars) for a store with three competitors within one mile, a population of 8,000 within one mile, and no drive-up window.
$
X
(c) Predict sales (in dollars) for a store with one competitor within one mile, a population of 3,000 within one mile, and a drive-up window.
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