Homework Help is Here – Start Your Trial Now!
Business
Economics
1. Data were collected on sales of mountain bikes 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), and x3 = advertised price (dollars per unit). A summary of the regression output is below. Variable (nickname) Intercept FloorSpace Competing Ads Price Coefficient 1225.44 11.52 -6.935 -0.1496 (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. (b-1) Put an X in the correct answer circle. The coefficient of Floor Space says that each additional square foot of floor space... O adds about 11.52 to sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-2) Put an X in the correct answer circle. The coefficient of Competing Ads says that each additional $1,000 of "competitors' advertising expenditures"... O reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-3) Put an X in the correct answer circle. The coefficient of Price says that each additional $1 of advertised price... reduces sales by about 0.1496 from sales (in thousands of dollars). reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). (c) The intercept is meaningful. (d) Make a prediction for Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200. O True O False

1. Data were collected on sales of mountain bikes 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), and x3 = advertised price (dollars per unit). A summary of the regression output is below. Variable (nickname) Intercept FloorSpace Competing Ads Price Coefficient 1225.44 11.52 -6.935 -0.1496 (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. (b-1) Put an X in the correct answer circle. The coefficient of Floor Space says that each additional square foot of floor space... O adds about 11.52 to sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-2) Put an X in the correct answer circle. The coefficient of Competing Ads says that each additional $1,000 of "competitors' advertising expenditures"... O reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-3) Put an X in the correct answer circle. The coefficient of Price says that each additional $1 of advertised price... reduces sales by about 0.1496 from sales (in thousands of dollars). reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). adds about 6.935 to sales (in thousands of dollars). (c) The intercept is meaningful. (d) Make a prediction for Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200. O True O False

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter4: Estimating Demand
Section: Chapter Questions
Problem 9E
See similar textbooks
icon
Related questions
Question
100%
1. Data were collected on sales of mountain bikes in 30 sporting goods stores. The regression model was y = total sales (thousands of dollars), *₁ = display floor space (square meters), 2 = competitors' advertising expenditures (thousands of dollars), and x3 = advertised price (dollars per unit). A summary of the regression output is below. Variable (nickname) Intercept FloorSpace Competing Ads Price Coefficient 1225.44 11.52 -6.935 -0.1496 (a) Write the fitted regression equation. Round your coefficient Competing Ads to 3 decimal places, coefficient Price to 4 decimal places, and other values to 2 decimal places. (b-1) Put an X in the correct answer circle. The coefficient of FloorSpace says that each additional square foot of floor space... O adds about 11.52 to sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-2) Put an X in the correct answer circle. The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures"... O reduces sales by about 6.935 from sales (in thousands of dollars). O takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). O takes away 0.1496 from sales (in thousands of dollars). (b-3) Put an X in the correct answer circle. The coefficient of Price says that each additional $1 of advertised price... reduces sales by about 0.1496 from sales (in thousands of dollars). O reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). (c) The intercept is meaningful. (d) Make a prediction for Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200. True False
Transcribed Image Text:1. Data were collected on sales of mountain bikes in 30 sporting goods stores. The regression model was y = total sales (thousands of dollars), *₁ = display floor space (square meters), 2 = competitors' advertising expenditures (thousands of dollars), and x3 = advertised price (dollars per unit). A summary of the regression output is below. Variable (nickname) Intercept FloorSpace Competing Ads Price Coefficient 1225.44 11.52 -6.935 -0.1496 (a) Write the fitted regression equation. Round your coefficient Competing Ads to 3 decimal places, coefficient Price to 4 decimal places, and other values to 2 decimal places. (b-1) Put an X in the correct answer circle. The coefficient of FloorSpace says that each additional square foot of floor space... O adds about 11.52 to sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). takes away 0.1496 from sales (in thousands of dollars). (b-2) Put an X in the correct answer circle. The coefficient of CompetingAds says that each additional $1,000 of "competitors' advertising expenditures"... O reduces sales by about 6.935 from sales (in thousands of dollars). O takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). O takes away 0.1496 from sales (in thousands of dollars). (b-3) Put an X in the correct answer circle. The coefficient of Price says that each additional $1 of advertised price... reduces sales by about 0.1496 from sales (in thousands of dollars). O reduces sales by about 6.935 from sales (in thousands of dollars). takes away 11.52 from sales (in thousands of dollars). O adds about 6.935 to sales (in thousands of dollars). (c) The intercept is meaningful. (d) Make a prediction for Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200. True False
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Knowledge Booster
Regression Model
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, economics and related others by exploring similar questions and additional content below.
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
Managerial Economics: Applications, Strategies an…
Managerial Economics: Applications, Strategies an…
Economics
ISBN:
9781305506381
Author:
James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:
Cengage Learning
SEE MORE TEXTBOOKS