Observations are taken on sales of a certain mountain bike in 30 sporting goods
ID: 3044901 • Letter: O
Question
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). Coefficient 1,265.54 10.45 -6.865 -0.1437 Predictor Intercept FloorSpace CompetingAds Price (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.) FloorSpace + CompetingAds + Price (b-1) The coefficient of FloorSpace says that each additional square foot of floor space O adds about 10.45 to sales (in thousands of dollars) O adds about 6.865 to sales (in thousands of dollars). O takes away 0.1496 from sales (in thousands of dollars). O takes away 10.45 from sales (in thousands of dollars). (b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures O adds about 6.865 to sales (in thousands of dollars). O reduces sales by about 6.865 from sales (in thousands of dollars). O takes away10.45 from sales (in thousands of dollars) O takes away 0.1437 from sales (in thousands of dollars). (b-3) The coefficient of Price says that each additional $1 of advertised price O reduces sales by about 6.865 from sales (in thousands of dollars). O takes away 10.45 from sales (in thousands of dollars) O reduces sales by about 0.1437 from sales (in thousands of dollars). O adds about 6.865 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 O False O True (d) Make a prediction for Sales when Floorspace-61, CompetingAds-86, and Price = 1048 Enter your answer in thousands. Round your answer to 2 decimal places.) thousand SalesExplanation / Answer
(a)
According to the data given, the fitted regression equation:
y = 1265.54 + 10.45*FloorSpace - 6.865*CompetingAds - 0.1437*Price
(b-1)
The coefficient of floor space says that each additional square foot of floor space adds about 10.45 to sales ( in thousand dollars).
(b-2)
The coefficient of competing ads says that each additional 1000 dollars of ads expenditure redcues sales by about 6.865 from sales ( in thousand dollars).
(b-3)
The coefficient of Price says that each additional 1 dollar of advertising price redcues sales by about 0.1437 from sales ( in thousand dollars).
(d)
Putting values in the regression equation we get:
y = 1265.54 + 10.45*61 - 6.865*86 - 0.1437*1048 = 1162.0024 thousand dollars
Hope this helps !
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