Table 3.

Regression coefficients and validation parameters for the model in the regression analysis.

Model Term	Regression Coefficients
	Rs1–2	Rs2–3	Rs3–4	Rs4–5	Rs5–6	Rs6–7	Rs7–8	Analysis Time
constant	3.092	1.297	0.848	2.594	0.000	1.275	0.877	23.085
x1, %B initial	−0.026	0.122	0.076	0.056	0.098	0.006	−0.121	−0.620
x2,%B end	−0.043	−0.051	0.384	−0.335	−0.008	−0.627	0.134	−3.039
x3, pH	0.241	0.701	0.132	0.070	1.096	−0.274	−0.126	−0.617
x 1 x 1	−0.020	−0.067	0.442	−0.140	0.044	−0.246	−0.084	−0.672
x 1 x 2	−0.087	−0.178	0.046	−0.214	−0.097	−0.135	0.227	−0.774
x 1 x 3	0.251	0.070	−0.188	0.154	0.201	0.132	−0.027	−0.025
x 2 x 2	−0.041	0.041	0.432	−0.119	0.553	−0.257	−0.107	0.208
x 2 x 3	0.103	0.193	−0.015	0.008	0.733	−0.035	0.331	0.085
x 3 x 3	−2.821	−0.582	0.109	−1.218	2.030	1.131	0.147	0.366
Model Validation
R 2	0.9743	0.9153	0.7414	0.9370	0.8794	0.9401	0.8679	0.9375
R 2 (adjustedford.f)	0.9281	0.7629	0.2758	0.8236	0.6624	0.8324	0.6301	0.8260
SE	0.4005	0.3234	0.4443	0.3008	0.8749	0.3461	0.1908	1.0064
MAE	0.1987	0.1477	0.1983	0.1392	0.3958	0.1577	0.0830	0.5456

Note: SE, standard error of estimation; MAE, mean absolute error; Values in bold red text indicate that the corresponding variables had a significant effect (p value < 0.05).