Reference no: EM132851904

Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X₁ = display floor space (square meters), X₂ = competitors' advertising expenditures (thousands of dollars), X₃ = advertised price (dollars per unit).

PredictorCoefficientIntercept1,276.84FloorSpace13.82CompetingAds-6.892Price-0.1446

(a) Write the fitted regression equation. (Round your coefficient CompetingAds to 3 decimal places, coefficient Price to 4 decimal places, and other values to 2 decimal places. Negative values should be indicated by a minus sign.)

y

ˆ

y^ =  +  * FloorSpace +  * CompetingAds +  * Price

(b-1) The coefficient of FloorSpace says that each additional square foot of floor space

multiple choice 1

• takes away 0.1496 from sales (in thousands of dollars).
• takes away 13.82 from sales (in thousands of dollars).
• adds about 13.82 to sales (in thousands of dollars). 
• Correct adds about 6.892 to sales (in thousands of dollars).

(b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures" takes away 0.1446 from sales (in thousands of dollars).

(b-3) The coefficient of Price says that each additional $1 of advertised price adds about 6.892 to sales (in thousands of dollars).

(c) The intercept is not meaningful, since a mountain bike cannot sell for zero, which will happen if all the variables are zero.

False

(d) Make a prediction for Sales when FloorSpace = 101, CompetingAds = 115, and Price = 1,222. (Enter your answer in thousands. Round your answer to 2 decimal places.)

Sales         $  thousand