Multiple Linear Regression - Estimated Regression Equation |
y[t] = + 1.48357142857143 -0.0407472111651671dummy[t] + 0.00359133126934983trend[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) | 1.48357142857143 | 0.005196 | 285.5389 | 0 | 0 |
dummy | -0.0407472111651671 | 0.079351 | -0.5135 | 0.609583 | 0.304792 |
trend | 0.00359133126934983 | 0.00153 | 2.3477 | 0.022387 | 0.011193 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.897701072443381 |
R-squared | 0.805867215465997 |
Adjusted R-squared | 0.79905553881568 |
F-TEST (value) | 118.306733692155 |
F-TEST (DF numerator) | 2 |
F-TEST (DF denominator) | 57 |
p-value | 0 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 0.0336719156278326 |
Sum Squared Residuals | 0.064626480416729 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 1.43 | 1.48357142857144 | -0.053571428571436 |
2 | 1.43 | 1.48357142857143 | -0.0535714285714282 |
3 | 1.43 | 1.48357142857143 | -0.0535714285714285 |
4 | 1.43 | 1.48357142857143 | -0.0535714285714285 |
5 | 1.43 | 1.48357142857143 | -0.0535714285714285 |
6 | 1.43 | 1.48357142857143 | -0.0535714285714285 |
7 | 1.44 | 1.48357142857143 | -0.0435714285714284 |
8 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
9 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
10 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
11 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
12 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
13 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
14 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
15 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
16 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
17 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
18 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
19 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
20 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
21 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
22 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
23 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
24 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
25 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
26 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
27 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
28 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
29 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
30 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
31 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
32 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
33 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
34 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
35 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
36 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
37 | 1.48 | 1.48357142857143 | -0.00357142857142840 |
38 | 1.57 | 1.48357142857143 | 0.0864285714285717 |
39 | 1.58 | 1.48357142857143 | 0.0964285714285717 |
40 | 1.58 | 1.48357142857143 | 0.0964285714285717 |
41 | 1.58 | 1.48357142857143 | 0.0964285714285717 |
42 | 1.58 | 1.48357142857143 | 0.0964285714285717 |
43 | 1.59 | 1.59725146198830 | -0.00725146198830409 |
44 | 1.6 | 1.60084279325765 | -0.000842793257653915 |
45 | 1.6 | 1.60443412452700 | -0.00443412452700375 |
46 | 1.61 | 1.60802545579635 | 0.00197454420364643 |
47 | 1.61 | 1.61161678706570 | -0.00161678706570341 |
48 | 1.61 | 1.61520811833505 | -0.00520811833505324 |
49 | 1.62 | 1.61879944960440 | 0.00120055039559693 |
50 | 1.63 | 1.62239078087375 | 0.00760921912624688 |
51 | 1.63 | 1.62598211214310 | 0.00401788785689705 |
52 | 1.64 | 1.62957344341245 | 0.0104265565875472 |
53 | 1.64 | 1.63316477468180 | 0.0068352253181974 |
54 | 1.64 | 1.63675610595115 | 0.00324389404884756 |
55 | 1.64 | 1.64034743722050 | -0.000347437220502276 |
56 | 1.64 | 1.64393876848985 | -0.00393876848985211 |
57 | 1.65 | 1.6475300997592 | 0.00246990024079807 |
58 | 1.65 | 1.65112143102855 | -0.00112143102855177 |
59 | 1.65 | 1.65471276229790 | -0.0047127622979016 |
60 | 1.65 | 1.65830409356725 | -0.00830409356725144 |