## 3 Results
### Two Variables
#### 3.1.4 The Evaluation Results of the Other Literature with Two Variables  
The evaluation results of the other literature with two variables are in Table 4. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Source** & **Purpose** & **Reported Equations** & **Contour and Response Surface Plots** & **Adequate Equations** & **Normality Test** & **Constant Variance** & **Influential Data** \\ \hline \multirow{3}{*}{[PERSON] et al. [2011]} & Extraction of & & & & & & \\  & \(x_{\text{1-}}\) temperature & & & & & & \\  & \(x_{\text{2-}}\) ethanol (\(\%\)) & & & & & & \\ \hline \multirow{3}{*}{[PERSON] et al. [2012]} & _Allora_ & _random_seconds & \(\text{V}_{\text{acc}}\) (moisture) = \(f(x_{\text{1}},x_{\text{2}},x_{\text{2}}^{\text{2}})\), & Curved surface & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}},x_{\text{2}}^{\text{2}})\) & Passed & \multirow{3}{*}{No} \\  & \(x_{\text{1-}}\) temperature & \(\text{V}_{\text{acc}}\) (color) = \(f(x_{\text{1}},x_{\text{2}})\) & Plane & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Passed & \multirow{3}{*}{No} \\  & \(x_{\text{2-}}\) time & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Plane & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Passed & \multirow{3}{*}{No} \\  & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Plane & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Passed & \multirow{3}{*}{No} \\  & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Plane & \(\text{V}_{\text{acc}}\) = \(f(x_{\text{1}},x_{\text{2}})\) & Passed & \multirow{3}{*}{No} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The results of the evaluation of the adequate RSM equations for two variables. In the study of [PERSON] et al. [31], the complete datasets of the 5-CQA (chlorogenic acid) response and two variables were listed. When these datasets were obtained using modern regression, it was found that the adequate equation is in the same form as reported in the literature. One influential factor was found. In this adequate equation, the relationship between the variables x\({}_{1}\) and response was linear, and that between the variables x\({}_{2}\) and response was quadratic. However, the response surface plot presented in the study is a curve for both variables [31]. In the evaluation of the literature data of [PERSON] et al. [32], there are five responses. For the y\({}_{\text{OC}}\) and y\({}_{\text{AE}}\) responses, the literature report has the same results as the adequate equations calculated in this study. For the y\({}_{\text{MC}}\) and y\({}_{\text{BF}}\) responses, the authors recommended the use of the complete model and the curve distribution in their response surface plots. However, the results of the adequate equations calculated by modern regression are different. For the response y\({}_{\text{AE}}\), the authors reported that the x\({}_{1}\) and x\({}_{2}\) variables have a linear relationship. In this study, only x\({}_{2}\) variables significantly affect the y response. The authors' selection of their equations in the literature was limited to the whole linear form (x\({}_{1}\), x\({}_{2}\)) or whole quadratic form (x\({}_{1}\), x\({}_{2}\), x\({}_{1}\)\({}^{2}\), x\({}_{2}\)\({}^{2}\), and x\({}_{1}\)x\({}_{2}\)) with the sequential model of the response's square. The effect of individual variables was not considered, so the results are different from modern regression. The selection of these variables in the study was carried out to use the results of the sequential model of the ANOVA table to justify the significant effects of the variables. When the linear or quadratic forms have a significant effect, all variables in the linear form (x\({}_{1}\) and x\({}_{2}\)) or the whole quadratic form (x\({}_{1}\)\({}^{2}\), x\({}_{2}\)\({}^{2}\), x\({}_{1}\)x\({}_{2}\)) are accepted in these RSM models. The significant effect of each variable on response does not need to be tested individually. These problems have been illustrated in Section 2.5 of this study.