Table 5.
The regression model analysis of variance.
| Source | Sum of squares | df | Mean square | F value | P value | Significance |
|---|---|---|---|---|---|---|
| Model | 1.34 | 14 | 0.0956 | 28.08 | <0.0001 | ∗∗∗ |
| A | 0.025 | 1 | 0.025 | 7.35 | 0.0169 | ∗ |
| B | 0.2028 | 1 | 0.2028 | 59.57 | <0.0001 | ∗∗∗ |
| C | 0.0302 | 1 | 0.0302 | 8.87 | 0.01 | ∗ |
| D | 0.0936 | 1 | 0.0936 | 27.5 | 0.0001 | ∗∗ |
| AB | 0.0035 | 1 | 0.0035 | 1.04 | 0.3251 | |
| AC | 0.0025 | 1 | 0.0025 | 0.7197 | 0.4105 | |
| AD | 0.0146 | 1 | 0.0146 | 4.3 | 0.057 | |
| BC | 0.0039 | 1 | 0.0039 | 1.15 | 0.3022 | |
| BD | 0.0036 | 1 | 0.0036 | 1.06 | 0.3212 | |
| CD | 0.0009 | 1 | 0.0009 | 0.2644 | 0.6152 | |
| A2 | 0.2357 | 1 | 0.2357 | 69.24 | <0.0001 | ∗∗∗ |
| B2 | 0.3953 | 1 | 0.3953 | 116.12 | <0.0001 | ∗∗∗ |
| C2 | 0.1176 | 1 | 0.1176 | 34.53 | <0.0001 | ∗∗∗ |
| D2 | 0.6441 | 1 | 0.6441 | 189.21 | <0.0001 | ∗∗∗ |
| Residual | 0.0477 | 14 | 0.0034 | |||
| Lack of fit | 0.0372 | 10 | 0.0037 | 1.42 | 0.3918 | |
| Pure error | 0.0104 | 4 | 0.0026 | |||
| Cor total | 1.39 | 28 |
Note. ∗P < 0.05, the difference is significant; ∗∗P < 0.01, the difference is highly significant; ∗∗∗P < 0.001, the difference is extremely significant.