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# Ford Mustang Case 7 Essay

3121 words - 13 pages

11
Ford Mustang Case 7
Applied Managerial Statistics

To determine the factors that affect Selling Price of Ford Mustangs, we need to select the independent factors or variables to test the hypothesis to see if these factors do have any affect on the selling price of Ford Mustangs cars. In this case I have selected nine Independent variables that we have used to study the relationship with selling price are (1) Whether the car is a convertible or not convertible (2) Transmission Type (3) Presence or absence of air conditioning (4) GT Model or not (5) Private owner or dealer owner (6) Age of car (7) Mileage (8) # of cylinders (9) Color.
We want to start by conducting a hypothesis test to ...view middle of the document...

28084 | 0.0000 | 5840.293 | 8722.107 |
CONVERT | 3194.4 | 1324.978 | 2.410909 | 0.021642 | 498.7108 | 5890.089 |
Conclusion: Reject the null hypothesis, since the P-value rounded up, (0.022) is less than the significance level (0.05). The sample provides enough evidence to conclude that the mean price depends on whether the car is a convertible.
We run the same independent test on each of the other eight variables in a similar manner as we did above; we conducted the hypothesis test to study the affect of Independent variable “TRANS” on the Selling Price. Following are the Null and Alternate Hypothesis set to study the relationship between the transmission type and price.
The null hypothesis tested is
H0: The mean price does not depend on the transmission type.
The alternative hypothesis is
H1: The mean price depends on the transmission type.
SUMMARY OUTPUT | | | | | |
| | | | | | |
Regression Statistics | | | | | |
Multiple R | 0.147477 | | | | | |
R Square | 0.021749 | | | | | |
Adjusted R Square | -0.00789 | | | | | |
Standard Error | 3798.379 | | | | | |
Observations | 35 | | | | | |
| | | | | | |
ANOVA | | | | | | |
| df | SS | MS | F | Significance F | |
Regression | 1 | 10585400 | 10585400 | 0.733687 | 0.397868 | |
Residual | 33 | 4.76E+08 | 14427683 | | | |
Total | 34 | 4.87E+08 |   |   |   | |
| | | | | | |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 7744.857 | 828.8743 | 9.343826 | 0.0000 | 6058.498 | 9431.216 |
TRANS | 1122.571 | 1310.565 | 0.856555 | 0.397868 | -1543.8 | 3788.939 |
Conclusion: Fails to reject the null hypothesis, since the P-value (0.398) is greater than the significance level (0.05). The sample does not provide enough evidence to conclude that the mean price depends on the transmission type.
Now we set the Null and Alternate Hypothesis to study the relationship between the independent variables “AIR” and the dependent variable “SELLING PRICE”.
The null hypothesis tested is
H0: The mean price does not depend on, presence or absence of air conditioning.
The alternative hypothesis is
H1: The mean price depends on, presence or absence of air conditioning.
SUMMARY OUTPUT | | | | | |
| | | | | | |
Regression Statistics | | | | | |
Multiple R | 0.108856 | | | | | |
R Square | 0.01185 | | | | | |
Adjusted R Square | -0.01809 | | | | | |
Standard Error | 3817.55 | | | | | |
Observations | 35 | | | | | |
| | | | | | |
ANOVA | | | | | | |
| df | SS | MS | F | Significance F | |
Regression | 1 | 5767203 | 5767203 | 0.395727 | 0.533635 | |
Residual | 33 | 4.81E+08 | 14573689 | | | |
Total | 34 | 4.87E+08 |   |   |   | |
| | | | | | |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 6545 | 2699.416 | 2.424599 | 0.020964 | 1052.993 | 12037.01 |
AIR | 1748.818 | 2780.013 | 0.629068 | 0.533635 | -3907.17 | 7404.801 |
Conclusion: Fails to reject the null hypothesis, since the P-value (0.534) is...

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