Finding the Best Car Value: Regression Analysis and Conclusions

Running Header: Finding the Best Car Value 1
Finding the Best Car Value
Student’s name: Obaid Alshaali
Student’s ID:
Institution:

Finding the Best Car Value 2
1. Treating Cost/Mile as the dependent variable, develop an estimated regression with
Family-Sedan and Upscale-Sedan as the independent variables. Discuss your
findings.
Figure 1: Regression analysis
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.87
R Square 0.76
Adjusted R Square 0.75
Standard Error 0.05
Observations 54
ANOVA
df SS MS F Significance F
Regression 2 0.43 0.22 79.89 0.00
Residual 51 0.14 0.00
Total 53 0.57
Coefficients Standard Error t Stat P-value
Intercept 0.52 0.01 36.25 0.00
Family-sedan 0.12 0.02 6.42 0.00
Upscale-sedan 0.23 0.02 12.54 0.00
All factors kept constant, the base cost per mile of a car is 0.52. The base cost per mile is
statistically significant at p = 0.05. For a Family-Sedan, the cost per mile increases by 0.12 units.
On the other hand, for an upscale sedan, the cost per mile increases by 0.23 units.

Finding the Best Car Value 3
2. Treating Value Score as the dependent variable, develop an estimated regression
equation using Cost/Mile, Road-Test Score, Predicted Reliability, Family-Sedan and
Upscale-Sedan as the independent variables.
Figure 2: Regression analysis
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.97
R Square 0.94
Adjusted R Square 0.93
Standard Error 0.07
Observations 54
ANOVA
df SS MS F Significance F
Regression 5 3.60 0.72 138.81 0.00
Residual 48 0.25 0.01
Total 53 3.85
Coefficients Standard Error t Stat P-value
Intercept 1.37 0.14 9.82 0.00
Family-sedan 0.02 0.04 0.60 0.55
Upscale-Sedan 0.07 0.05 1.27 0.21
Cost/Mile -2.27 0.19 -11.69 0.00
Road-Test Score 0.01 0.00 8.48 0.00
Predicted Reliability 0.17 0.01 15.93 0.00
The regression equation that is derived from the regression model is:
Value_Score = 1.37 + 0.02Family-sedan + 0.07Upscale-sedan – 2.27Cost_mile +
0.01Road_Test_Score + 0.17Predicted_reliability