Multiple Linear Regression - Estimated Regression Equation |
Cons[t] = + 199.335492893705 + 0.252706741242155Inc[t] -1.32549945613131Price[t] + 3.05427647897147M1[t] + 10.6390359513754M2[t] + 8.08171646467381M3[t] + 4.35127025569707M4[t] + 16.0989684657797M5[t] + 9.49042015525736M6[t] + 13.8548509021607M7[t] + 18.0368950324733M8[t] + 20.161172163332M9[t] + 14.3421516844835M10[t] + 14.7173481828168M11[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) | 199.335492893705 | 229.229433 | 0.8696 | 0.448511 | 0.224255 |
Inc | 0.252706741242155 | 2.416107 | 0.1046 | 0.9233 | 0.46165 |
Price | -1.32549945613131 | 0.124255 | -10.6675 | 0.001761 | 0.00088 |
M1 | 3.05427647897147 | 9.370784 | 0.3259 | 0.765885 | 0.382942 |
M2 | 10.6390359513754 | 10.523355 | 1.011 | 0.386482 | 0.193241 |
M3 | 8.08171646467381 | 16.309506 | 0.4955 | 0.654257 | 0.327128 |
M4 | 4.35127025569707 | 20.673167 | 0.2105 | 0.846779 | 0.423389 |
M5 | 16.0989684657797 | 23.117614 | 0.6964 | 0.536289 | 0.268144 |
M6 | 9.49042015525736 | 35.065713 | 0.2706 | 0.804215 | 0.402108 |
M7 | 13.8548509021607 | 38.059359 | 0.364 | 0.739978 | 0.369989 |
M8 | 18.0368950324733 | 41.66477 | 0.4329 | 0.694319 | 0.347159 |
M9 | 20.161172163332 | 34.910244 | 0.5775 | 0.604084 | 0.302042 |
M10 | 14.3421516844835 | 25.907147 | 0.5536 | 0.61844 | 0.30922 |
M11 | 14.7173481828168 | 18.298824 | 0.8043 | 0.480067 | 0.240033 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.991340221475236 |
R-squared | 0.982755434714571 |
Adjusted R-squared | 0.908028985144378 |
F-TEST (value) | 13.1513733138283 |
F-TEST (DF numerator) | 13 |
F-TEST (DF denominator) | 3 |
p-value | 0.0281722914747159 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 7.1502322723593 |
Sum Squared Residuals | 153.377464646066 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 99.2 | 92.9510661815308 | 6.24893381846919 |
2 | 99 | 102.082564602192 | -3.08256460219183 |
3 | 100 | 100.137937869463 | -0.13793786946344 |
4 | 111.6 | 110.105449580208 | 1.49455041979237 |
5 | 122.2 | 127.287695560429 | -5.08769556042862 |
6 | 117.6 | 117.6 | -1.19869392189997e-15 |
7 | 121.1 | 121.1 | 1.33573707650214e-16 |
8 | 136 | 136 | 1.33573707650214e-16 |
9 | 154.2 | 154.2 | 3.55618312575245e-16 |
10 | 153.6 | 153.6 | 5.77662917500277e-16 |
11 | 158.5 | 158.5 | -3.10515502199848e-16 |
12 | 140.6 | 140.6 | -8.84708972748172e-17 |
13 | 136.2 | 142.448933818469 | -6.24893381846919 |
14 | 168 | 164.917435397808 | 3.08256460219183 |
15 | 154.3 | 154.162062130537 | 0.137937869463439 |
16 | 149 | 150.494550419792 | -1.49455041979237 |
17 | 165.5 | 160.412304439571 | 5.08769556042862 |