| Multiple Linear Regression - Estimated Regression Equation |
| Y[t] = + 2324.06337310277 -226.385033602657X[t] -451.374973256309M1[t] -635.461053323771M2[t] -583.133697991392M3[t] -694.556342659014M4[t] -555.478987326639M5[t] -609.464131994259M6[t] -532.074276661885M7[t] -515.434421329508M8[t] -460.85706599713M9[t] -319.717210664754M10[t] -118.389855332377M11[t] -1.76485533237686t + 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) | 2324.06337310277 | 44.029939 | 52.7837 | 0 | 0 |
| X | -226.385033602657 | 41.037226 | -5.5166 | 0 | 0 |
| M1 | -451.374973256309 | 53.942919 | -8.3676 | 0 | 0 |
| M2 | -635.461053323771 | 53.941479 | -11.7806 | 0 | 0 |
| M3 | -583.133697991392 | 53.931287 | -10.8125 | 0 | 0 |
| M4 | -694.556342659014 | 53.922166 | -12.8807 | 0 | 0 |
| M5 | -555.478987326639 | 53.914117 | -10.303 | 0 | 0 |
| M6 | -609.464131994259 | 53.907141 | -11.3058 | 0 | 0 |
| M7 | -532.074276661885 | 53.901237 | -9.8713 | 0 | 0 |
| M8 | -515.434421329508 | 53.896405 | -9.5634 | 0 | 0 |
| M9 | -460.85706599713 | 53.892648 | -8.5514 | 0 | 0 |
| M10 | -319.717210664754 | 53.889963 | -5.9328 | 0 | 0 |
| M11 | -118.389855332377 | 53.888353 | -2.1969 | 0.029316 | 0.014658 |
| t | -1.76485533237686 | 0.240551 | -7.3367 | 0 | 0 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.861322441473346 |
| R-squared | 0.741876348185605 |
| Adjusted R-squared | 0.723024620805902 |
| F-TEST (value) | 39.3532291891914 |
| F-TEST (DF numerator) | 13 |
| F-TEST (DF denominator) | 178 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 152.417759557721 |
| Sum Squared Residuals | 4135148.87028996 |
