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Use the Following to Answer Questions

Question 21

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Use the following to answer questions :
Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided.
Single Predictor Model:
The regression equation is Price = 13.8 - 0.0912 Mileage
Use the following to answer questions : Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided. Single Predictor Model: The regression equation is Price = 13.8 - 0.0912 Mileage     Two Predictor Model: The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age     S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0% Analysis of Variance    -Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria. The regression equation is Price = 15.3 - 1.71 Age     S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Analysis of Variance
Two Predictor Model:
The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age
Use the following to answer questions : Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided. Single Predictor Model: The regression equation is Price = 13.8 - 0.0912 Mileage     Two Predictor Model: The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age     S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0% Analysis of Variance    -Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria. The regression equation is Price = 15.3 - 1.71 Age     S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Analysis of Variance
S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0%
Analysis of Variance
Use the following to answer questions : Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided. Single Predictor Model: The regression equation is Price = 13.8 - 0.0912 Mileage     Two Predictor Model: The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age     S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0% Analysis of Variance    -Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria. The regression equation is Price = 15.3 - 1.71 Age     S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Analysis of Variance
-Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria.
The regression equation is Price = 15.3 - 1.71 Age
Use the following to answer questions : Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided. Single Predictor Model: The regression equation is Price = 13.8 - 0.0912 Mileage     Two Predictor Model: The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age     S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0% Analysis of Variance    -Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria. The regression equation is Price = 15.3 - 1.71 Age     S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Analysis of Variance
S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4%
Analysis of Variance
Use the following to answer questions : Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output from two models are provided. Single Predictor Model: The regression equation is Price = 13.8 - 0.0912 Mileage     Two Predictor Model: The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age     S = 1.39445 R-Sq = 89.0% R-Sq(adj) = 88.0% Analysis of Variance    -Regression output for the model that only uses Age as a predictor in the model is provided. Assuming that the residuals for this single predictor model do not indicate any problems, is this model an improvement over the model that uses both Age and Mileage as predictors? Statistically justify your answer by discussing at least two quantitative criteria. The regression equation is Price = 15.3 - 1.71 Age     S = 1.37179 R-Sq = 88.9% R-Sq(adj) = 88.4% Analysis of Variance

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Yes this model is an improvement over th...

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