Multiple Linear Regression - Estimated Regression Equation |
y[t] = + 1.96610169491525 + 1.03389830508475x[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) | 1.96610169491525 | 0.070508 | 27.8847 | 0 | 0 |
x | 1.03389830508475 | 0.546155 | 1.893 | 0.063344 | 0.031672 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.241228855223658 |
R-squared | 0.0581913605925166 |
Adjusted R-squared | 0.0419532806027325 |
F-TEST (value) | 3.58363554244876 |
F-TEST (DF numerator) | 1 |
F-TEST (DF denominator) | 58 |
p-value | 0.063344176187855 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 0.541584574696143 |
Sum Squared Residuals | 17.0122033898305 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 1.3 | 1.96610169491526 | -0.666101694915256 |
2 | 1.2 | 1.96610169491525 | -0.766101694915254 |
3 | 1.6 | 1.96610169491525 | -0.366101694915254 |
4 | 1.7 | 1.96610169491525 | -0.266101694915254 |
5 | 1.5 | 1.96610169491525 | -0.466101694915254 |
6 | 0.9 | 1.96610169491525 | -1.06610169491525 |
7 | 1.5 | 1.96610169491525 | -0.466101694915254 |
8 | 1.4 | 1.96610169491525 | -0.566101694915254 |
9 | 1.6 | 1.96610169491525 | -0.366101694915254 |
10 | 1.7 | 1.96610169491525 | -0.266101694915254 |
11 | 1.4 | 1.96610169491525 | -0.566101694915254 |
12 | 1.8 | 1.96610169491525 | -0.166101694915254 |
13 | 1.7 | 1.96610169491525 | -0.266101694915254 |
14 | 1.4 | 1.96610169491525 | -0.566101694915254 |
15 | 1.2 | 1.96610169491525 | -0.766101694915254 |
16 | 1 | 1.96610169491525 | -0.966101694915254 |
17 | 1.7 | 1.96610169491525 | -0.266101694915254 |
18 | 2.4 | 1.96610169491525 | 0.433898305084746 |
19 | 2 | 1.96610169491525 | 0.0338983050847458 |
20 | 2.1 | 1.96610169491525 | 0.133898305084746 |
21 | 2 | 1.96610169491525 | 0.0338983050847458 |
22 | 1.8 | 1.96610169491525 | -0.166101694915254 |
23 | 2.7 | 1.96610169491525 | 0.733898305084746 |
24 | 2.3 | 1.96610169491525 | 0.333898305084746 |
25 | 1.9 | 1.96610169491525 | -0.0661016949152543 |
26 | 2 | 1.96610169491525 | 0.0338983050847458 |
27 | 2.3 | 1.96610169491525 | 0.333898305084746 |
28 | 2.8 | 1.96610169491525 | 0.833898305084746 |
29 | 2.4 | 1.96610169491525 | 0.433898305084746 |
30 | 2.3 | 1.96610169491525 | 0.333898305084746 |
31 | 2.7 | 1.96610169491525 | 0.733898305084746 |
32 | 2.7 | 1.96610169491525 | 0.733898305084746 |
33 | 2.9 | 1.96610169491525 | 0.933898305084746 |
34 | 3 | 3 | -3.01475966586751e-17 |
35 | 2.2 | 1.96610169491525 | 0.233898305084746 |
36 | 2.3 | 1.96610169491525 | 0.333898305084746 |
37 | 2.8 | 1.96610169491525 | 0.833898305084746 |
38 | 2.8 | 1.96610169491525 | 0.833898305084746 |
39 | 2.8 | 1.96610169491525 | 0.833898305084746 |
40 | 2.2 | 1.96610169491525 | 0.233898305084746 |
41 | 2.6 | 1.96610169491525 | 0.633898305084746 |
42 | 2.8 | 1.96610169491525 | 0.833898305084746 |
43 | 2.5 | 1.96610169491525 | 0.533898305084746 |
44 | 2.4 | 1.96610169491525 | 0.433898305084746 |
45 | 2.3 | 1.96610169491525 | 0.333898305084746 |
46 | 1.9 | 1.96610169491525 | -0.0661016949152543 |
47 | 1.7 | 1.96610169491525 | -0.266101694915254 |
48 | 2 | 1.96610169491525 | 0.0338983050847458 |
49 | 2.1 | 1.96610169491525 | 0.133898305084746 |
50 | 1.7 | 1.96610169491525 | -0.266101694915254 |
51 | 1.8 | 1.96610169491525 | -0.166101694915254 |
52 | 1.8 | 1.96610169491525 | -0.166101694915254 |
53 | 1.8 | 1.96610169491525 | -0.166101694915254 |
54 | 1.3 | 1.96610169491525 | -0.666101694915254 |
55 | 1.3 | 1.96610169491525 | -0.666101694915254 |
56 | 1.3 | 1.96610169491525 | -0.666101694915254 |
57 | 1.2 | 1.96610169491525 | -0.766101694915254 |
58 | 1.4 | 1.96610169491525 | -0.566101694915254 |
59 | 2.2 | 1.96610169491525 | 0.233898305084746 |
60 | 2.9 | 1.96610169491525 | 0.933898305084746 |