(d) Make a prediction for Sales when FloorSpace = 118, Competing Ads = 109, and Price = 1,336. (Enter your answer in thousands. Round your answer to 2 decimal places.) Section Exercise 13 - 2 (Algo) 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). C c Section Exercise 13-2 (Algo) 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). Predictor Coefficient Intercept FloorSpace CompetingAds 1,294.83 11.43 -6.935 Price -0.1434
(d) Make a prediction for Sales when FloorSpace = 118, Competing Ads = 109, and Price = 1,336. (Enter your answer in thousands. Round your answer to 2 decimal places.) Section Exercise 13 - 2 (Algo) 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). C c Section Exercise 13-2 (Algo) 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). Predictor Coefficient Intercept FloorSpace CompetingAds 1,294.83 11.43 -6.935 Price -0.1434
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Related questions
Question
Typed

Transcribed Image Text:=
(d) Make a prediction for Sales when FloorSpace =118, CompetingAds 109, and Price 1,336. (Enter your answer
in thousands. Round your answer to 2 decimal places.) Section Exercise 13 - 2 (Algo) 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
=
), x=display floor space (square meters), x2 competitors' advertising expenditures (thousands of dollars), x3 =
advertised price (dollars per unit).
C
Section Exercise 13-2 (Algo)
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).
Predictor
Intercept
FloorSpace
CompetingAds
Price
Coefficient
1,294.83
11.43
-6.935
-0.1434

Transcribed Image Text:Section Exercise 13-2 (Algo)
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)
advertised price (dollars per unit)
Predictor
Intercept
Floor Space
CompetingAds
Price
Coefficient
1,294.83
11.43
-6.935
-0.1434
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