es (b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures" O takes away 0.1461 from sales (in thousands of dollars). Ⓒadds about 6.848 to sales (in thousands of dollars). O takes away 13.74 from sales (in thousands of dollars). O reduces sales by about 6.848 from sales (in thousands of dollars). (b-3) The coefficient of Price says that each additional $1 of advertised price reduces sales by about 0.1461 from sales (in thousands of dollars) O takes away 13.74 from sales (in thousands of dollars). adds about 6.848 to sales (in thousands of dollars). O reduces sales by about 6.848 from 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=100, CompetingAds = 102, and Price = 1,023. (Enter your answer in thousands. Round your answer to 2 decimal places.) Sales thousand

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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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), X₁ =
advertised price (dollars per unit).
Predictor
Intercept
FloorSpace
CompetingAds
Price
Coefficient
1,243.88
13.74
-6.848
-0.1461
(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+
(b-1) The coefficient of FloorSpace says that each additional square foot of floor space
O takes away 13.74 from sales (in thousands of dollars)
O adds about 13.74 to sales (in thousands of dollars)
adds about 6.848 to sales (in thousands of dollars)
takes away 01496 from sales (in thousands of dollars)
(b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors advertising expenditures"
takes away 01461 from sales (in thousands of dollars)
O adds about 6 848 to sales (in thousands of dollars)
O takes away 13.74 from sales (in thousands of dollars)
O reduces sales by about 6.848 from sales (in thousands of dollars).
(b-3) The coefficient of Price says that each additional $1 of advertised price
Jallment.
*Price
Transcribed Image Text: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), X₁ = advertised price (dollars per unit). Predictor Intercept FloorSpace CompetingAds Price Coefficient 1,243.88 13.74 -6.848 -0.1461 (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+ (b-1) The coefficient of FloorSpace says that each additional square foot of floor space O takes away 13.74 from sales (in thousands of dollars) O adds about 13.74 to sales (in thousands of dollars) adds about 6.848 to sales (in thousands of dollars) takes away 01496 from sales (in thousands of dollars) (b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors advertising expenditures" takes away 01461 from sales (in thousands of dollars) O adds about 6 848 to sales (in thousands of dollars) O takes away 13.74 from sales (in thousands of dollars) O reduces sales by about 6.848 from sales (in thousands of dollars). (b-3) The coefficient of Price says that each additional $1 of advertised price Jallment. *Price
(b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures"
O takes away 0.1461 from sales (in thousands of dollars).
Ⓒ adds about 6.848 to sales (in thousands of dollars).
O takes away 13.74 from sales (in thousands of dollars).
O reduces sales by about 6.848 from sales (in thousands of dollars).
(b-3) The coefficient of Price says that each additional $1 of advertised price
reduces sales by about 0.1461 from sales (in thousands of dollars).
O takes away 13.74 from sales (in thousands of dollars).
adds about 6.848 to sales (in thousands of dollars).
reduces sales by about 6.848 from 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= 100, CompetingAds = 102, and Price = 1,023. (Enter your answer in thousands.
Round your answer to 2 decimal places.)
Sales
thousand
Transcribed Image Text:(b-2) The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures" O takes away 0.1461 from sales (in thousands of dollars). Ⓒ adds about 6.848 to sales (in thousands of dollars). O takes away 13.74 from sales (in thousands of dollars). O reduces sales by about 6.848 from sales (in thousands of dollars). (b-3) The coefficient of Price says that each additional $1 of advertised price reduces sales by about 0.1461 from sales (in thousands of dollars). O takes away 13.74 from sales (in thousands of dollars). adds about 6.848 to sales (in thousands of dollars). reduces sales by about 6.848 from 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= 100, CompetingAds = 102, and Price = 1,023. (Enter your answer in thousands. Round your answer to 2 decimal places.) Sales thousand
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