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A Local Truck Rental Company Wants to Use Regression to Predict

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A local truck rental company wants to use regression to predict the yearly maintenance expense (Y), in dollars, for a truck using the number of miles driven during the year A local truck rental company wants to use regression to predict the yearly maintenance expense (Y), in dollars, for a truck using the number of miles driven during the year   and the age of the truck in years   at the beginning of the year. To examine the relationship, the company has gathered the data on 15 trucks and regression analysis has been conducted. The regression output is presented below.   -(A) Estimate the regression model. How well does this model fit the given data? ​ (B) Is there a linear relationship between the two explanatory variables and the dependent variable at the 5% significance level? Explain how you arrived at your answer. ​ (C) Use the estimated regression model to predict the annual maintenance expense of a truck that is driven 14,000 miles per year and is 5 years old. ​ (D) Find a 95% prediction interval for the maintenance expense determined in (C). Use a t-multiple = 2. ​ (E) Find a 95% confidence interval for the maintenance expense for all trucks sharing the characteristics provided in (C). Use a t-multiple = 2. ​ (F) How do you explain the differences between the widths of the intervals in (D) and (E)? and the age of the truck in years A local truck rental company wants to use regression to predict the yearly maintenance expense (Y), in dollars, for a truck using the number of miles driven during the year   and the age of the truck in years   at the beginning of the year. To examine the relationship, the company has gathered the data on 15 trucks and regression analysis has been conducted. The regression output is presented below.   -(A) Estimate the regression model. How well does this model fit the given data? ​ (B) Is there a linear relationship between the two explanatory variables and the dependent variable at the 5% significance level? Explain how you arrived at your answer. ​ (C) Use the estimated regression model to predict the annual maintenance expense of a truck that is driven 14,000 miles per year and is 5 years old. ​ (D) Find a 95% prediction interval for the maintenance expense determined in (C). Use a t-multiple = 2. ​ (E) Find a 95% confidence interval for the maintenance expense for all trucks sharing the characteristics provided in (C). Use a t-multiple = 2. ​ (F) How do you explain the differences between the widths of the intervals in (D) and (E)? at the beginning of the year. To examine the relationship, the company has gathered the data on 15 trucks and regression analysis has been conducted. The regression output is presented below. A local truck rental company wants to use regression to predict the yearly maintenance expense (Y), in dollars, for a truck using the number of miles driven during the year   and the age of the truck in years   at the beginning of the year. To examine the relationship, the company has gathered the data on 15 trucks and regression analysis has been conducted. The regression output is presented below.   -(A) Estimate the regression model. How well does this model fit the given data? ​ (B) Is there a linear relationship between the two explanatory variables and the dependent variable at the 5% significance level? Explain how you arrived at your answer. ​ (C) Use the estimated regression model to predict the annual maintenance expense of a truck that is driven 14,000 miles per year and is 5 years old. ​ (D) Find a 95% prediction interval for the maintenance expense determined in (C). Use a t-multiple = 2. ​ (E) Find a 95% confidence interval for the maintenance expense for all trucks sharing the characteristics provided in (C). Use a t-multiple = 2. ​ (F) How do you explain the differences between the widths of the intervals in (D) and (E)?
-(A) Estimate the regression model. How well does this model fit the given data?

(B) Is there a linear relationship between the two explanatory variables and the dependent variable at the 5% significance level? Explain how you arrived at your answer.

(C) Use the estimated regression model to predict the annual maintenance expense of a truck that is driven 14,000 miles per year and is 5 years old.

(D) Find a 95% prediction interval for the maintenance expense determined in (C). Use a t-multiple = 2.

(E) Find a 95% confidence interval for the maintenance expense for all trucks sharing the characteristics provided in (C). Use a t-multiple = 2.

(F) How do you explain the differences between the widths of the intervals in (D) and (E)?


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