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regression_statistics_w2.xlsxRegression Statistics
| Calculation of Regression Statistics (amounts in thousands) | ||||||||||
| Advertising (x) | Sales (y) | xy | x2 | y2 | ||||||
| 9 | 15 | 135 | 81 | 225 | ||||||
| 19 | 20 | 380 | 361 | 400 | ||||||
| 11 | 14 | 154 | 121 | 196 | ||||||
| 14 | 16 | 224 | 196 | 256 | ||||||
| 23 | 25 | 575 | 529 | 625 | ||||||
| 12 | 20 | 240 | 144 | 400 | ||||||
| 12 | 20 | 240 | 144 | 400 | ||||||
| 22 | 23 | 506 | 484 | 529 | ||||||
| 7 | 14 | 98 | 49 | 196 | ||||||
| 13 | 22 | 286 | 169 | 484 | ||||||
| 15 | 18 | 270 | 225 | 324 | ||||||
| 17 | 18 | 306 | 289 | 324 | ||||||
| SUMS (S) | 174 | 225 | 3,414 | 2,792 | 4,359 | |||||
| Using the formulas below, we substitute from the table above and obtain an intercept (a) of 10.5836 and a slope (b) of .5632 | ||||||||||
| y= | a + bx | |||||||||
| a= | 10.5836431227 | |||||||||
| b= | 0.563197026 |
Regression Report
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.7799828575 | |||||||
| R Square | 0.6083732581 | |||||||
| Adjusted R Square | 0.5692105839 | |||||||
| Standard Error | 2.3436222084 | |||||||
| Observations | 12 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 1 | 85.3243494424 | 85.3243494424 | 15.5345177665 | 0.0027686531 | |||
| Residual | 10 | 54.9256505576 | 5.4925650558 | |||||
| Total | 11 | 140.25 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 10.5836431227 | 2.1796087802 | 4.8557535732 | 0.0006656245 | 5.7271721382 | 15.4401141072 | 5.7271721382 | 15.4401141072 |
| X Variable 1 | 0.563197026 | 0.142893168 | 3.9413852598 | 0.0027686531 | 0.2448112081 | 0.8815828439 | 0.2448112081 | 0.8815828439 |
