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20. A data set has the annual revenue for 15 rental car companies (in units of millions of dollars), which is the response variable, as a function of the number of cars in use (in units of thousands of vehicles) and locations (in units of hundreds of locations.) The results of a linear regression model with both predictors included gives: The regression equation is Revenue = 10.6 + 0.894 Cars - 0.191 Location Predictor T P Constant Cars Coef SE Coef 10.597 8.552 0.89427 0.0774 1.24 0.239 11.55 0.000 Location -0.1914 0.1026 -1.87 0.087 Standard Error = 20.77 R = 94.2% Adjusted R = 93.2% a.) Estimate the revenue for a company with twelve thousand cars and one hundred locations. b.) The actual revenue for the company in part (a.) was $28 million. Is this an unusually high revenue for a company of that size? Explain your answer in a sentence. c.) If you were to drop one of the predictors from this model, which one would you drop? Explain why in a sentence.

20. A data set has the annual revenue for 15 rental car companies (in units of millions of dollars), which is the response variable, as a function of the number of cars in use (in units of thousands of vehicles) and locations (in units of hundreds of locations.) The results of a linear regression model with both predictors included gives: The regression equation is Revenue = 10.6 + 0.894 Cars - 0.191 Location Predictor T P Constant Cars Coef SE Coef 10.597 8.552 0.89427 0.0774 1.24 0.239 11.55 0.000 Location -0.1914 0.1026 -1.87 0.087 Standard Error = 20.77 R = 94.2% Adjusted R = 93.2% a.) Estimate the revenue for a company with twelve thousand cars and one hundred locations. b.) The actual revenue for the company in part (a.) was $28 million. Is this an unusually high revenue for a company of that size? Explain your answer in a sentence. c.) If you were to drop one of the predictors from this model, which one would you drop? Explain why in a sentence.

College Algebra
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...
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20 solve all parts plzz
20. A data set has the annual revenue for 15 rental car companies (in units of millions of dollars), which is the response variable, as a function of the number of cars in use (in units of thousands of vehicles) and locations (in units of hundreds of locations.) The results of a linear regression model with both predictors included gives: The regression equation is Revenue = 10.6 + 0.894 Cars - 0.191 Location Predictor SE Coef Coef 10.597 8.552 P Constant Cars Location 1.24 0.239 11.55 0.000 -1.87 0.087 0.89427 0.0774 -0.1914 0.1026 Standard Error = 20.77 R = 94.2% Adjusted R? = 93.2% a.) Estimate the revenue for a company with twelve thousand cars and one hundred locations. b.) The actual revenue for the company in part (a.) was $28 million. Is this an unusually high revenue for a company of that size? Explain your answer in a sentence. c.) If you were to drop one of the predictors from this model, which one would you drop? Explain why in a sentence. d.) When a regression was run with revenue as response and location as the only predictor, the p- value for the coefficient was 0.004, and the R2 was 78%. Why might this happen?
Transcribed Image Text:20. A data set has the annual revenue for 15 rental car companies (in units of millions of dollars), which is the response variable, as a function of the number of cars in use (in units of thousands of vehicles) and locations (in units of hundreds of locations.) The results of a linear regression model with both predictors included gives: The regression equation is Revenue = 10.6 + 0.894 Cars - 0.191 Location Predictor SE Coef Coef 10.597 8.552 P Constant Cars Location 1.24 0.239 11.55 0.000 -1.87 0.087 0.89427 0.0774 -0.1914 0.1026 Standard Error = 20.77 R = 94.2% Adjusted R? = 93.2% a.) Estimate the revenue for a company with twelve thousand cars and one hundred locations. b.) The actual revenue for the company in part (a.) was $28 million. Is this an unusually high revenue for a company of that size? Explain your answer in a sentence. c.) If you were to drop one of the predictors from this model, which one would you drop? Explain why in a sentence. d.) When a regression was run with revenue as response and location as the only predictor, the p- value for the coefficient was 0.004, and the R2 was 78%. Why might this happen?
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