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Table 4

Analysis of variance (ANOVA) and regression analysis for the quadratic model for the preparation of membrane

Analysis of variance (ANOVA)
Model formula in RSM (X1, X2, X3, X4)DFSum of squaresMean squaresF-valueProbability (P)
FO 4785.3 196.32 19 0.6095 2.00 × 10−17 
TWI 30.8 5.13 0.8168 0.565845 
PQ 146.0 36.5 5.8156 0.1457 
Residuals 29 182.0 6.28 – – 
Lack of fit 10 72.3 7.23 1.2523 0.322 
Pure error 19 109.7 5.77 – – 
Regression analysis for the quadratic model
ParameterCoefficient estimate
Std errort valuePr(>|t|)
(Intercept) 70.485 0.56019 125.8228 <2.2 × 10−16 
X1 4.225 1.02277 4.131 0.00028 
X2 9.74167 1.02277 9.5248 1.97 × 10−10 
X3 2.575 1.02277 2.5177 0.01759 
X4 26.04167 1.02277 25.462 <2.2 × 10−16 
X2^2 4.63583 1.71142 2.7088 0.01121 
X3^2 5.23583 1.71142 3.0594 0.00474 
X4^2 −3.46417 1.71142 −2.0242 0.05225 
Analysis of variance (ANOVA)
Model formula in RSM (X1, X2, X3, X4)DFSum of squaresMean squaresF-valueProbability (P)
FO 4785.3 196.32 19 0.6095 2.00 × 10−17 
TWI 30.8 5.13 0.8168 0.565845 
PQ 146.0 36.5 5.8156 0.1457 
Residuals 29 182.0 6.28 – – 
Lack of fit 10 72.3 7.23 1.2523 0.322 
Pure error 19 109.7 5.77 – – 
Regression analysis for the quadratic model
ParameterCoefficient estimate
Std errort valuePr(>|t|)
(Intercept) 70.485 0.56019 125.8228 <2.2 × 10−16 
X1 4.225 1.02277 4.131 0.00028 
X2 9.74167 1.02277 9.5248 1.97 × 10−10 
X3 2.575 1.02277 2.5177 0.01759 
X4 26.04167 1.02277 25.462 <2.2 × 10−16 
X2^2 4.63583 1.71142 2.7088 0.01121 
X3^2 5.23583 1.71142 3.0594 0.00474 
X4^2 −3.46417 1.71142 −2.0242 0.05225 

F-statistic: 56.47 on 14 and 29, DF, p-value: <2.00 × 10−16, Multiple R2: 0.9646, Adjusted R2: 0.9475, Predicted R2: 0.9347, Lack of fit: 0.322061.

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