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florida1014 florida1014
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A month ago
Use the following to answer the questions below:

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

PredictorCoefSE CoefTP
Constant13.77510.693019.880.000
Mileage-0.0911670.009718-9.380.000

Two Predictor Model:
The regression equation is Price = 15.2 - 0.0101 Mileage - 1.55 Age

PredictorCoefSE CoefTP
Constant15.21740.611224.900.000
Mileage-0.010050.01977-0.510.616
Age-1.54660.3508-4.410.000

S = 1.39445       R-Sq = 89.0%        R-Sq(adj) = 88.0%

Analysis of Variance

SourceDFSSMSFP
Regression2346.11173.0689.000.000
Residual Error2242.781.94
Total24388.89

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

PredictorCoefSE CoefTP
Constant15.29120.584026.180.000
Age-1.71260.1264-13.550.000
S = 1.37179        R-Sq = 88.9%        R-Sq(adj) = 88.4%

Analysis of Variance

SourceDFSSMSFP
Regression1345.61345.61183.660.000
Residual Error2343.281.88
Total24388.89
Textbook 
Statistics: Unlocking the Power of Data

Statistics: Unlocking the Power of Data


Edition: 3rd
Authors:
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mkql12mkql12
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florida1014 Author
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A month ago
Smart ... Thanks!
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You make an excellent tutor!
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2 hours ago
Thanks
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