Table 4.

Results of regression analysis and ANOVA for the response surface quadratic model

Formula	NAT-SLN formulations			SD	CV%	Adequate precision for ANOVA	Remarks
	R-squared	Adjusted R-squared	Predicted R-squared
R1
Linear model	0.9072	0.8857	0.8114	2.90
2FI model	0.9253	0.8804	0.6400	2.79
Quadratic model	0.9945	0.9875	0.9261	0.96	2.84	43.500	Suggested
Cubic model	0.9991	0.9963	–	0.52			Aliased
R2
Linear model	0.7989	0.7525	0.6399	3.03
2FI model	0.98054	0.6886	0.2527	3.39
Quadratic model	0.9744	0.9414	0.9120	1.47	6.66	18.249	Suggested
Cubic model	0.9777	0.9107	–	1.82			Aliased
R3
Linear model	0.9157	0.8984	0.8348	3.95
2FI model	0.9684	0.9495	0.8695	2.87
Quadratic model	0.9901	0.9774	0.8461	1.86	2.93	32.245	Suggested
Cubic model	0.9997	0.9988	–	0.43			Aliased

Note: Underlined entries refer to “the best fit model terms”.

Abbreviation: CV%, coefficient of variation.