Table 2.
ANOVA for response surface quadratic model.
| Variables | Sun of squares | DF | Mean square | F value | P value |
|---|---|---|---|---|---|
| X 1 | 0.2646 | 1 | 0.2646 | 3.3678 | 0.0864b |
| X 2 | 0.6801 | 1 | 0.6800 | 8.6558 | 0.0101a |
| X 3 | 0.0204 | 1 | 0.0204 | 0.2599 | 0.6176b |
| X 4 | 0.1504 | 1 | 0.1504 | 1.9145 | 0.1867b |
| X 1 X 2 | 0.0256 | 1 | 0.0256 | 0.3258 | 0.5766b |
| X 1 X 3 | 0.81 | 1 | 0.81 | 10.3096 | 0.0058a |
| X 1 X 4 | 0.007225 | 1 | 0.0072 | 0.09196 | 0.7659b |
| X 2 X 3 | 1.3225 | 1 | 1.3225 | 16.8326 | 0.0009a |
| X 2 X 4 | 0.3306 | 1 | 0.3306 | 4.2082 | 0.0581b |
| X 3 X 4 | 1.3806 | 1 | 1.3806 | 17.5724 | 0.0008a |
| X 1 2 | 0.9240 | 1 | 0.9240 | 11.7606 | 0.0037a |
| X 2 2 | 0.1384 | 1 | 0.1384 | 1.7619 | 0.2042b |
| X 3 2 | 3.7507 | 1 | 3.7507 | 47.7390 | <0.0001a |
| X 4 2 | 4.3566 | 1 | 4.3566 | 55.4506 | <0.0001a |
| Model | 12.3418 | 14 | 0.8816 | 11.2204 | <0.0001a |
| Residual | 1.1785 | 15 | 0.0786 | ||
| Lack of fit | 0.8548 | 10 | 0.0855 | 1.3202 | 0.4001 |
| Pure error | 0.3237 | 5 | 0.0647 | ||
| Cor total | 13.5204 | 29 | |||
| R 2 = 0.9128 | |||||
| R adj 2 = 0.8315 | |||||
| C.V.% = 3.3429 |
aSignificance (P < 0.05); b nonsignificance (P > 0.05).