Multiple Linear Regression - Estimated Regression Equation |
Numeracy[t] = -13.6327 + 16.3117Geslacht[t] -3.36748Drugs[t] -0.0252995Fruit[t] + 0.575631Alcohol[t] + 6.71419Gebgewicht[t] -5.03669Inter[t] + e[t] |
Warning: you did not specify the column number of the endogenous series! The first column was selected by default. |
Multiple Linear Regression - Ordinary Least Squares | |||||
Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
(Intercept) | -13.63 | 17.57 | -7.7580e-01 | 0.4518 | 0.2259 |
Geslacht | +16.31 | 23.09 | +7.0640e-01 | 0.4924 | 0.2462 |
Drugs | -3.368 | 3.22 | -1.0460e+00 | 0.3147 | 0.1574 |
Fruit | -0.0253 | 2.78 | -9.1020e-03 | 0.9929 | 0.4964 |
Alcohol | +0.5756 | 2.941 | +1.9570e-01 | 0.8479 | 0.4239 |
Gebgewicht | +6.714 | 5.386 | +1.2470e+00 | 0.2345 | 0.1173 |
Inter | -5.037 | 6.769 | -7.4410e-01 | 0.47 | 0.235 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.4794 |
R-squared | 0.2298 |
Adjusted R-squared | -0.1256 |
F-TEST (value) | 0.6466 |
F-TEST (DF numerator) | 6 |
F-TEST (DF denominator) | 13 |
p-value | 0.6926 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 5.325 |
Sum Squared Residuals | 368.6 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 6 | 4.679 | 1.321 |
2 | 7 | 9.074 | -2.074 |
3 | 2 | 8.262 | -6.262 |
4 | 11 | 10.42 | 0.5828 |
5 | 13 | 8.86 | 4.14 |
6 | 3 | 1.128 | 1.872 |
7 | 17 | 9.268 | 7.732 |
8 | 10 | 10.42 | -0.4172 |
9 | 4 | 5.686 | -1.686 |
10 | 12 | 9.17 | 2.83 |
11 | 7 | 9.461 | -2.461 |
12 | 11 | 9.842 | 1.158 |
13 | 3 | 7.376 | -4.376 |
14 | 5 | 8.514 | -3.514 |
15 | 1 | 9.867 | -8.867 |
16 | 12 | 9.1 | 2.9 |
17 | 18 | 8.718 | 9.282 |
18 | 8 | 7.171 | 0.8291 |
19 | 6 | 4.822 | 1.178 |
20 | 1 | 5.167 | -4.167 |