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The following results are from data where the dependent variable is the selling price of used cars, the independent variables are similar to those in the above regression along with some additional variables. The data were split into 2 samples and the following regression results were obtained from the split data. If we wanted to test for hetero

The following results are from data where the dependent variable is the selling price of used cars, the independent variables are similar to those in the above regression along with some additional variables. The data were split into 2 samples and the following regression results were obtained from the split data. If we wanted to test for hetero

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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17) The following results are from data where the dependent variable is the selling price of used cars, the independent variables are similar to those in the above regression along with some additional variables. The data were split into 2 samples and the following regression results were obtained from the split data. If we wanted to test for heteroscedasticity, what is the test statistic? (please round your answer to 2 decimal places) **I explicitly need to know the test statistic**
Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.846 0.715 0.653 872.9 Observations 49 ANOVA df SS MS Regression 6. Significance F 76575468 8508385 11.2 Residual 1.03933E-08 40 30479336 761983 Total 49 107054804 Coefficients Standard Error t Stat P-value Intercept MSRP_Amt 17270.81 2684.71 6.43 0.00 0.35 0.06 Manual 5.55 0.00 384.14 309.31 Convertible 1.24 0.22 -814.13 375.34 -2.17 0.04 VIN8_6Cylinder Mileage_Sale ModelYearAge_Months CondReptAmt RepairAmt InventoryAge_Days -637.40 452.57 -1.41 0.17 -64.41 14.82 -4.35 0.00 -276.45 41.09 -6.73 0.00 -0.50 0.49 -1.02 0.31 1.52 0.70 2.17 0.04 -7.91 10.17 -0.78 0.44 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.724 0.524 0.423 Standard Error 1622.0 Observations 52 ANOVA df MS Significance F Regression Residual 116147955 12905328 4.90 0.000104741 40 105247338 2631183 Total 49 221395293 Coefficients Standard Error t Stat P-value Intercept MSRP_Amt 13992.20 3169.78 4.41 0.00 0.19 0.07 2.72 0.01 Manual 629.14 459.84 1.37 0.18 Convertible -920.90 1060.78 -0.87 0.39 VIN8_6Cylinder Mileage_Sale ModelYearAge_Months CondReptAmt RepairAmt InventoryAge_Days -1251.81 752.26 -1.66 0.10 -49.71 13.24 -3.75 0.00 -153.04 55.28 -2.77 0.01 -0.49 0.32 -1.53 0.13 -1.09 1.09 -0.99 0.33 -19.88 7.84 -2,54 0.01
Transcribed Image Text:Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.846 0.715 0.653 872.9 Observations 49 ANOVA df SS MS Regression 6. Significance F 76575468 8508385 11.2 Residual 1.03933E-08 40 30479336 761983 Total 49 107054804 Coefficients Standard Error t Stat P-value Intercept MSRP_Amt 17270.81 2684.71 6.43 0.00 0.35 0.06 Manual 5.55 0.00 384.14 309.31 Convertible 1.24 0.22 -814.13 375.34 -2.17 0.04 VIN8_6Cylinder Mileage_Sale ModelYearAge_Months CondReptAmt RepairAmt InventoryAge_Days -637.40 452.57 -1.41 0.17 -64.41 14.82 -4.35 0.00 -276.45 41.09 -6.73 0.00 -0.50 0.49 -1.02 0.31 1.52 0.70 2.17 0.04 -7.91 10.17 -0.78 0.44 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.724 0.524 0.423 Standard Error 1622.0 Observations 52 ANOVA df MS Significance F Regression Residual 116147955 12905328 4.90 0.000104741 40 105247338 2631183 Total 49 221395293 Coefficients Standard Error t Stat P-value Intercept MSRP_Amt 13992.20 3169.78 4.41 0.00 0.19 0.07 2.72 0.01 Manual 629.14 459.84 1.37 0.18 Convertible -920.90 1060.78 -0.87 0.39 VIN8_6Cylinder Mileage_Sale ModelYearAge_Months CondReptAmt RepairAmt InventoryAge_Days -1251.81 752.26 -1.66 0.10 -49.71 13.24 -3.75 0.00 -153.04 55.28 -2.77 0.01 -0.49 0.32 -1.53 0.13 -1.09 1.09 -0.99 0.33 -19.88 7.84 -2,54 0.01
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