Regression Analysis: Price versus Mileage, Liter Analysis of Variance Source DF
ID: 3156910 • Letter: R
Question
Regression Analysis: Price versus Mileage, Liter
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 2 25823830697 12911915348 196.48 0.000
Mileage 1 1381011542 1381011542 21.02 0.000
Liter 1 24218240322 24218240322 368.54 0.000
Error 801 52637552164 65714797
Lack-of-Fit 799 52623358855 65861525 9.28 0.102
Pure Error 2 14193309 7096655
Total 803 78461382861
Model Summary
S R-sq R-sq(adj) R-sq(pred)
8106.47 32.91% 32.75% 32.32%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 9427 1095 8.61 0.000
Mileage -0.1600 0.0349 -4.58 0.000 1.00
Liter 4968 259 19.20 0.000 1.00
Regression Equation
Price = 9427 - 0.1600 Mileage + 4968 Liter
Regress Price on Mileage and Liter. Call this Model 1. This regression does not seem to satisfy one of the assumptions of the regression model. What assumption is violated?
The residuals are not normally distributed.
The regression coefficients are not significant.
Price is not correlated with either Mileage or Liter.
The mean of the error term (the residual) is not equal to zero.
The residuals are not normally distributed.
B)The regression coefficients are not significant.
C)Price is not correlated with either Mileage or Liter.
D)The mean of the error term (the residual) is not equal to zero.
Explanation / Answer
c) Price is not correlated with either Mileage or Liter.