Question: For this question, use the following multiple regression output (which may differ from the output in other questions, even though the variables are the same).
For this question, use the following multiple regression output (which may differ from the output in other questions, even though the variables are the same).
| SUMMARY OUTPUT | ||||||
| Regression Statistics | ||||||
| Multiple R | 0.507 | |||||
| R Square | 0.257 | |||||
| Adjusted R Square | 0.217 | |||||
| Standard Error | 5319.659 | |||||
| Observations | 100 | |||||
| ANOVA | ||||||
| df | SS | MS | F | Significance F | ||
| Regression | 5 | 918149733.6 | 183629946.7 | 6.489 | 3.175E-05 | |
| Residual | 94 | 2660085040 | 28298777.02 | |||
| Total | 99 | 3578234773 | ||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
| Intercept | 9714.244 | 3289.053 | 2.954 | 0.0040 | 3183.751 | 16244.736 |
| Annual Income ($1000) | 87.421 | 18.063 | 4.840 | 5.082E-06 | 51.557 | 123.284 |
| Household Size | -145.809 | 270.677 | -0.539 | 0.5914 | -683.244 | 391.627 |
| Education | -676.427 | 335.456 | -2.016 | 0.0466 | -1342.483 | -10.371 |
| TV Hours | 42.242 | 31.228 | 1.353 | 0.1794 | -19.762 | 104.247 |
| Age | -72.153 | 52.101 | -1.385 | 0.1694 | -175.601 | 31.295 |
Develop the estimated regression equation relating all of the independent variables included in the data to annual charges. If required, round your answer to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
Estimated Amount Charged = + *Annual Income ($1000s)+ *Household Size+ *Education+ *TV+ *Age
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