Table 6.

Regression model coefficient significance model.

Name	Various	Sum of squares		Degree of freedom		Mean square		f-value		p-value		Significant or not
CS	A	15.96		1		15.96		43.63		< 0.0001		Yes
	B	33.82		1		33.82		92.48		< 0.0001		Yes
	C	147.66		1		147.66		403.75		< 0.0001		Yes
	D	317.77		1		317.77		868.9		< 0.0001		Yes
	AB	1.09		1		1.09		2.97		0.1053		No
	AC	11.78		1		11.78		32.22		< 0.0001		Yes
	AD	40.99		1		40.99		112.09		< 0.0001		Yes
	BC	0.0086		1		0.0086		0.0234		0.8805		No
	BD	7.28		1		7.28		19.9		0.0005		Yes
	CD	7.52		1		7.52		20.57		0.0004		Yes
	A2	54.6		1		54.6		149.3		< 0.0001		Yes
	B2	21.23		1		21.23		58.04		< 0.0001		Yes
	C2	50.66		1		50.66		138.53		< 0.0001		Yes
	D2	28.91		1		28.91		79.04		< 0.0001		Yes
	Residual	5.49		15		0.3657
	Lack of fit	4.67		10		0.467
	Pure error	0.8161		5		0.1632
STS	A	0.0315		1		0.0315		29.37		< 0.0001		Yes
	B	0.152		1		0.152		141.55		< 0.0001		Yes
	C	0.5673		1		0.5673		528.30		< 0.0001		Yes
	D	0.1552		1		0.1552		144.53		< 0.0001		Yes
	AB	6.25E-06		1		6.25E-06		0.0058		0.9402		No
	AC	0.0127		1		0.0127		11.79		0.0037		Yes
	AD	0.0002		1		0.0002		0.1455		0.7082		No
	BC	0.0023		1		0.0023		2.10		0.1678		No
	BD	0.0189		1		0.0189		17.61		0.0008		Yes
	CD	0.2998		1		0.2998		279.13		< 0.0001		Yes
	A2	0.0518		1		0.0518		48.19		< 0.0001		Yes
	B2	0.1530		1		0. 1530		142.48		< 0.0001		Yes
	C2	0.0000		1		0.0000		0.0224		0.8829		No
	D2	0.0033		1		0. 0033		3.06		0.1009		No
	Residual	0.0161		15		0.0011
	Lack of fit	0.0126		10		0.0013
	Pure error	0.0035		5		0.0007