| Multiple Linear Regression - Estimated Regression Equation |
| Gebgewicht[t] = + 3.24223 + 0.165977Geslacht[t] + 0.0679231Drugs[t] + 0.205691Fruit[t] -0.0822616Sport[t] -0.0224932Alcohol[t] + e[t] |
| Multiple Linear Regression - Ordinary Least Squares | |||||
| Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
| (Intercept) | +3.242 | 0.2314 | +1.4010e+01 | 1.253e-09 | 6.266e-10 |
| Geslacht | +0.166 | 0.1944 | +8.5400e-01 | 0.4075 | 0.2037 |
| Drugs | +0.06792 | 0.2561 | +2.6520e-01 | 0.7947 | 0.3974 |
| Fruit | +0.2057 | 0.2152 | +9.5570e-01 | 0.3554 | 0.1777 |
| Sport | -0.08226 | 0.2277 | -3.6130e-01 | 0.7232 | 0.3616 |
| Alcohol | -0.02249 | 0.2354 | -9.5540e-02 | 0.9252 | 0.4626 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.3405 |
| R-squared | 0.116 |
| Adjusted R-squared | -0.1998 |
| F-TEST (value) | 0.3672 |
| F-TEST (DF numerator) | 5 |
| F-TEST (DF denominator) | 14 |
| p-value | 0.8626 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.4273 |
| Sum Squared Residuals | 2.557 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 3.2 | 3.476 | -0.2761 |
| 2 | 3.3 | 3.425 | -0.1254 |
| 3 | 3 | 3.509 | -0.5091 |
| 4 | 3.5 | 3.425 | 0.07458 |
| 5 | 3.7 | 3.614 | 0.08611 |
| 6 | 2.7 | 3.31 | -0.6101 |
| 7 | 3.6 | 3.509 | 0.09086 |
| 8 | 3.5 | 3.425 | 0.07458 |
| 9 | 3.8 | 3.476 | 0.3239 |
| 10 | 3.4 | 3.448 | -0.04792 |
| 11 | 3.7 | 3.386 | 0.3143 |
| 12 | 3.5 | 3.448 | 0.05208 |
| 13 | 2.8 | 3.326 | -0.5259 |
| 14 | 3.8 | 3.228 | 0.5721 |
| 15 | 4.3 | 3.614 | 0.6861 |
| 16 | 3.3 | 3.22 | 0.08027 |
| 17 | 3.6 | 3.408 | 0.1918 |
| 18 | 3.6 | 3.228 | 0.3721 |
| 19 | 3.3 | 3.682 | -0.3818 |
| 20 | 2.8 | 3.242 | -0.4422 |
