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Answer:
The estimated multiple regression equation is ^Y= -49.17 + 15.03X₁ + 0.17X₂ + 12.23X₃ + 14.29X₄ -2.96X₅
Step-by-step explanation:
Hello!
To estimate a model to predict if it is a good investment to open a Starbucks.
Using the information of 27 Starbucks stores, and given the variables:
Y: Annual net sales ($1000)
X₁: Monthly rent ($1000)
X₂: Inventory expenses ($1000)
X₃: Advertising expenses ($1000)
X₄: Monthly sales ($1000)
X₅: Number of competitor stores in the area.
The multiple regression model is
Y= β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄ + β₅X₅ + ε
Using a statistics software I've estimated the regression equation:
^Y= -49.17 + 15.03X₁ + 0.17X₂ + 12.23X₃ + 14.29X₄ -2.96X₅
Where:
b₀: -49.17 thousand dollars represents the estimated average annual net sales when the monthly rent, the inventory expenses, the advertising expenses, the monthly sales and the number of competitors in the area are zero.
b₁: 15.03 represents the variation in the estimated average annual sales when the monthly rent increases $1000 and all other variables remain constant.
b₂: 0.17 represents the variation in the estimated average annual sales when the inventory expenses increase $1000 and all other variables remain constant.
b₃: 12.23 represents the variation in the estimated average annual sales when the advertisement expenses increase $1000 and all other variables remain constant.
b₄: 14.29 represents the variation in the estimated average annual sales when the monthly sales increase $1000 and all other variables remain constant.
b₅: -2.96 represents the variation in the estimated average annual sales when the number of competitors in the area increase in one unit and all other variables remain constant.
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I hope this helps!
