Multiple Linear Regression - Estimated Regression Equation
Numeracy[t] = -18.6605 -3.24798Drugs[t] + 26.9945Geslacht[t] -0.309166Fruit[t] -2.31672Sport[t] + 0.729851Alcohol[t] + 8.37152Gebgewicht[t] -8.09407Inter[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-18.66 19.51-9.5640e-01 0.3577 0.1789
Drugs-3.248 3.297-9.8510e-01 0.344 0.172
Geslacht+26.99 28.61+9.4360e-01 0.364 0.182
Fruit-0.3092 2.874-1.0760e-01 0.9161 0.4581
Sport-2.317 3.504-6.6110e-01 0.521 0.2605
Alcohol+0.7298 3.016+2.4200e-01 0.8129 0.4064
Gebgewicht+8.371 6.05+1.3840e+00 0.1917 0.09583
Inter-8.094 8.323-9.7250e-01 0.35 0.175


Multiple Linear Regression - Regression Statistics
Multiple R 0.5068
R-squared 0.2569
Adjusted R-squared-0.1766
F-TEST (value) 0.5926
F-TEST (DF numerator)7
F-TEST (DF denominator)12
p-value 0.7508
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 5.444
Sum Squared Residuals 355.6


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1 6 5.974 0.02618
2 7 9.386-2.386
3 2 7.27-5.27
4 11 11.06-0.06051
5 13 9.051 3.949
6 3 0.6946 2.305
7 17 7.437 9.563
8 10 11.06-1.061
9 4 6.14-2.14
10 12 9.494 2.506
11 7 10.09-3.09
12 11 10.33 0.6693
13 3 6.794-3.794
14 5 7.587-2.587
15 1 9.218-8.218
16 12 9.695 2.305
17 18 9.333 8.667
18 8 5.912 2.088
19 6 5.692 0.3076
20 1 4.78-3.78