Table 2.
Variance analysis of parameters in regression equation.
| Variables | Sum of Squares | df | Mean Square | F-Value | p-Value |
|---|---|---|---|---|---|
| Model | 46.61 | 9 | 5.18 | 139.25 | <0.0001 |
| A | 10.51 | 1 | 10.51 | 282.61 | <0.0001 |
| B | 32.20 | 1 | 32.20 | 865.75 | <0.0001 |
| C | 1.15 | 1 | 1.15 | 31.06 | 0.0008 |
| AB | 0.11 | 1 | 0.11 | 2.93 | 0.1308 |
| AC | 1.36 | 1 | 1.36 | 36.49 | 0.0005 |
| BC | 0.16 | 1 | 0.16 | 4.41 | 0.0739 |
| A2 | 0.025 | 1 | 0.025 | 0.66 | 0.4425 |
| B2 | 0.048 | 1 | 0.048 | 1.28 | 0.2945 |
| C2 | 1.08 | 1 | 1.08 | 28.98 | 0.0010 |
| Residual | 0.26 | 7 | 0.037 | ||
| Lack of fit | 0.19 | 3 | 0.062 | 3.35 | 0.1365 |
| Pure error | 0.074 | 4 | 0.019 | ||
| Cor. Total | 46.87 | 16 |
R2 = 0.9944, R2Adj = 0.9873, R2Pred = 0.9339, C.V. = 0.76%.