## 3 Results and Discussion
As can be seen from the last column of Table 15, all \(p\)-values are greater than 0.05, and therefore, the data are normally distributed. In fact, this is also evident from Figures 1(a), 1(a), 1(a) and 1(a). The samples must have a common variance. To verify this, a homogeneity test (Test of Homogeneity of Variance) was carried out in SPSS, i.e., hypotheses of equality of population variances were tested using [PERSON]'s Test of Equality of Error Variances. For the condition of homogeneity of variances to be met, [PERSON]'s test should not be statistically significant, \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Tests of Normality**} \\  & \multicolumn{2}{c}{**Hydro**} & \multicolumn{2}{c}{**Kolmogorov–Smirnov****a**} & \multicolumn{2}{c}{**Shapiro–Wilk**} \\  & \multicolumn{2}{c}{**Module**} & \multicolumn{2}{c}{**Statistic**} & \multicolumn{2}{c}{**df**} & **Sig.** & **Statistic** & **df** & **Sig.** \\ \hline \multirow{4}{*}{ABTS} & 5 & 0.198 & 6 & 0.200 * & 0.950 & 6 & 0.739 \\ \cline{2-8}  & 10 & 0.148 & 17 & 0.200 * & 0.933 & 17 & 0.247 \\ \cline{2-8}  & 20 & 0.242 & 6 & 0.200 * & 0.805 & 6 & 0.066 \\ \hline \multirow{4}{*}{Alfa\_Gl} & 5 & 0.157 & 6 & 0.200 * & 0.962 & 6 & 0.836 \\ \cline{2-8}  & 10 & 0.130 & 17 & 0.200 * & 0.968 & 17 & 0.791 \\ \cline{2-8}  & 20 & 0.360 & 6 & 0.140 & 0.755 & 6 & 0.122 \\ \hline \multirow{4}{*}{AChE} & 5 & 0.231 & 6 & 0.200 * & 0.904 & 6 & 0.399 \\ \cline{2-8}  & 10 & 0.288 & 17 & 0.140 & 0.882 & 17 & 0.234 \\ \cline{2-8}  & 20 & 0.210 & 6 & 0.200 * & 0.934 & 6 & 0.608 \\ \hline \multirow{4}{*}{TPC} & 5 & 0.174 & 6 & 0.200 * & 0.966 & 6 & 0.868 \\ \cline{2-8}  & 10 & 0.117 & 17 & 0.200 * & 0.977 & 17 & 0.928 \\ \cline{2-8}  & 20 & 0.205 & 6 & 0.200 * & 0.917 & 6 & 0.487 \\ \hline \multirow{4}{*}{TFC} & 5 & 0.205 & 6 & 0.200 * & 0.954 & 6 & 0.771 \\ \cline{2-8}  & 10 & 0.149 & 17 & 0.200 * & 0.927 & 17 & 0.194 \\ \cline{2-8}  & 20 & 0.243 & 6 & 0.200 * & 0.863 & 6 & 0.198 \\ \hline \multirow{4}{*}{FRAP} & 5 & 0.214 & 6 & 0.200 * & 0.888 & 6 & 0.310 \\ \cline{2-8}  & 10 & 0.181 & 17 & 0.140 & 0.934 & 17 & 0.258 \\ \cline{2-8}  & 20 & 0.306 & 6 & 0.083 & 0.777 & 6 & 0.437 \\ \hline \multirow{4}{*}{CUPRAC} & 5 & 0.270 & 6 & 0.197 & 0.883 & 6 & 0.282 \\ \cline{2-8}  & 10 & 0.178 & 17 & 0.156 & 0.940 & 17 & 0.315 \\ \cline{2-8}  & 20 & 0.179 & 6 & 0.200 * & 0.916 & 6 & 0.475 \\ \hline \multirow{4}{*}{DPPH} & 5 & 0.188 & 6 & 0.200 * & 0.979 & 6 & 0.946 \\ \cline{2-8}  & 10 & 0.229 & 17 & 0.182 & 0.879 & 17 & 0.331 \\ \cline{1-1} \cline{2-8}  & 20 & 0.160 & 6 & 0.200 * & 0.924 & 6 & 0.532 \\ \hline \hline \end{tabular}  
* This is a lower bound of the true significance.
* Lilliefors Significance Correction.  
\end{table} 
Table 15: ANOVA test of normality. i.e., \(p\)-value > 0.05. The homogeneity test results obtained are presented in Table 16. They show that the homogeneity requirement is met. A numerical optimization is implemented, which aims to find a point that maximizes the desirability function. Table 17 presents the constraints under which the optimization was performed. In reality, the desired effect is for values of the independent factors that are in the studied range to obtain maximum values for responses. Table 18 shows that all goals are joined into one desirability function, which ix based on various responses and factors. The suitable optimum formulation (Hydro module of 20, Duration of 39.328 min, Temperature of 70 \({}^{\circ}\)C, and Extractant of 96.638%) with high desirability of 0.703 was selected. The Design Expert v.13 software returns a table of 100 possible solutions. For brevity, only the first three of them are presented here.