Multiple Linear Regression - Estimated Regression Equation |
y[t] = + 99.6478260869565 + 10.6035252643948x[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) | 99.6478260869565 | 2.484137 | 40.1137 | 0 | 0 |
x | 10.6035252643948 | 3.163372 | 3.352 | 0.001417 | 0.000709 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.402842176110845 |
R-squared | 0.162281818853721 |
Adjusted R-squared | 0.147838401937406 |
F-TEST (value) | 11.2356944200932 |
F-TEST (DF numerator) | 1 |
F-TEST (DF denominator) | 58 |
p-value | 0.00141709187417027 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 11.9135027882280 |
Sum Squared Residuals | 8232.02982373678 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 106.8 | 99.6478260869565 | 7.15217391304348 |
2 | 113.7 | 99.6478260869565 | 14.0521739130435 |
3 | 102.5 | 99.6478260869565 | 2.85217391304348 |
4 | 96.6 | 99.6478260869565 | -3.04782608695653 |
5 | 92.1 | 99.6478260869565 | -7.54782608695653 |
6 | 95.6 | 99.6478260869565 | -4.04782608695653 |
7 | 102.3 | 99.6478260869565 | 2.65217391304347 |
8 | 98.6 | 99.6478260869565 | -1.04782608695653 |
9 | 98.2 | 99.6478260869565 | -1.44782608695652 |
10 | 104.5 | 99.6478260869565 | 4.85217391304348 |
11 | 84 | 99.6478260869565 | -15.6478260869565 |
12 | 73.8 | 99.6478260869565 | -25.8478260869565 |
13 | 103.9 | 99.6478260869565 | 4.25217391304348 |
14 | 106 | 99.6478260869565 | 6.35217391304348 |
15 | 97.2 | 99.6478260869565 | -2.44782608695652 |
16 | 102.6 | 99.6478260869565 | 2.95217391304347 |
17 | 89 | 99.6478260869565 | -10.6478260869565 |
18 | 93.8 | 99.6478260869565 | -5.84782608695653 |
19 | 116.7 | 99.6478260869565 | 17.0521739130435 |
20 | 106.8 | 99.6478260869565 | 7.15217391304347 |
21 | 98.5 | 99.6478260869565 | -1.14782608695652 |
22 | 118.7 | 99.6478260869565 | 19.0521739130435 |
23 | 90 | 99.6478260869565 | -9.64782608695652 |
24 | 91.9 | 110.251351351351 | -18.3513513513513 |
25 | 113.3 | 110.251351351351 | 3.04864864864865 |
26 | 113.1 | 110.251351351351 | 2.84864864864864 |
27 | 104.1 | 110.251351351351 | -6.15135135135136 |
28 | 108.7 | 110.251351351351 | -1.55135135135135 |
29 | 96.7 | 110.251351351351 | -13.5513513513513 |
30 | 101 | 110.251351351351 | -9.25135135135135 |
31 | 116.9 | 110.251351351351 | 6.64864864864865 |
32 | 105.8 | 110.251351351351 | -4.45135135135135 |
33 | 99 | 110.251351351351 | -11.2513513513514 |
34 | 129.4 | 110.251351351351 | 19.1486486486487 |
35 | 83 | 110.251351351351 | -27.2513513513513 |
36 | 88.9 | 110.251351351351 | -21.3513513513513 |
37 | 115.9 | 110.251351351351 | 5.64864864864865 |
38 | 104.2 | 110.251351351351 | -6.05135135135135 |
39 | 113.4 | 110.251351351351 | 3.14864864864865 |
40 | 112.2 | 110.251351351351 | 1.94864864864865 |
41 | 100.8 | 110.251351351351 | -9.45135135135135 |
42 | 107.3 | 110.251351351351 | -2.95135135135135 |
43 | 126.6 | 110.251351351351 | 16.3486486486486 |
44 | 102.9 | 110.251351351351 | -7.35135135135135 |
45 | 117.9 | 110.251351351351 | 7.64864864864865 |
46 | 128.8 | 110.251351351351 | 18.5486486486487 |
47 | 87.5 | 110.251351351351 | -22.7513513513513 |
48 | 93.8 | 110.251351351351 | -16.4513513513514 |
49 | 122.7 | 110.251351351351 | 12.4486486486487 |
50 | 126.2 | 110.251351351351 | 15.9486486486487 |
51 | 124.6 | 110.251351351351 | 14.3486486486486 |
52 | 116.7 | 110.251351351351 | 6.44864864864865 |
53 | 115.2 | 110.251351351351 | 4.94864864864865 |
54 | 111.1 | 110.251351351351 | 0.848648648648642 |
55 | 129.9 | 110.251351351351 | 19.6486486486487 |
56 | 113.3 | 110.251351351351 | 3.04864864864865 |
57 | 118.5 | 110.251351351351 | 8.24864864864865 |
58 | 133.5 | 110.251351351351 | 23.2486486486487 |
59 | 102.1 | 110.251351351351 | -8.15135135135136 |
60 | 102.4 | 110.251351351351 | -7.85135135135135 |