Multiple Linear Regression - Estimated Regression Equation |
V1[t] = + 527.571 + 16.4286t + 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) | 527.571 | 126.37 | 4.175 | 0.00584705 | 0.00292353 |
t | 16.4286 | 25.0249 | 0.6565 | 0.535861 | 0.267931 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.258874 |
R-squared | 0.0670158 |
Adjusted R-squared | -0.0884816 |
F-TEST (value) | 0.430977 |
F-TEST (DF numerator) | 1 |
F-TEST (DF denominator) | 6 |
p-value | 0.535861 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 162.18 |
Sum Squared Residuals | 157814 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 399 | 544 | -145 |
2 | 499 | 560.429 | -61.4286 |
3 | 599 | 576.857 | 22.1429 |
4 | 699 | 593.286 | 105.714 |
5 | 799 | 609.714 | 189.286 |
6 | 759 | 626.143 | 132.857 |
7 | 659 | 642.571 | 16.4286 |
8 | 399 | 659 | -260 |