Given,
Y = 12.1075 - 1.7687 X1
| Source |
DF |
Sum of Squares | Mean Square | F Statistic | P-value |
|---|---|---|---|---|---|
| Regression (between ŷiand yi) |
1 |
238.0704 |
238.0704 |
1.4850 |
0.2485 |
| Residual (between yiand ŷi) |
11 |
1763.4496 |
160.3136 |
||
| Total(between yiand yi) |
12 |
2001.5200 |
166.7933 |
|
Coeff |
SE | t-stat | lower t0.025(11) | upper t0.975(11) |
Stand Coeff |
p-value |
VIF |
|
|---|---|---|---|---|---|---|---|---|
| b | 12.1075 | 3.5593 | 3.4016 | 4.2734 | 19.9415 | 0.000 | 0.005912 | |
| X1 | -1.7687 | 1.4514 | -1.2186 | -4.9633 | 1.4258 | -0.3449 | 0.2485 | 1.0000 |
R square (R2) equals 0.1189. It
means that the predictors (Xi) explain 11.9% of the
variance of Y.
Adjusted R square equals 0.03885.
The coefficient of multiple correlation (R) equals 0.3449. It means that there is a weak direct relationship between the predicted data (ŷ) and the observed data (y).
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