## 3 Results
### Concurrent Screening for Energy Consumption and Intervention Costs  
The intervention costs (IC), which have also been generated using the supersaturated trial planner as a guide, are listed in Table 5. Intervention costs are usually conducive to the local range of available brands of electromechanical equipment/systems as well as to market standing and negotiation efforts. Therefore, ICs are always subjective to the time and area of the performed study and, hence, it precludes any further commenting on this issue. This strengthens the need for the analysis that follows because we realize that each study is custom-based on the mere specifics of the examined apartment unit. First, we assess the prospect of a potential correlation between the two response vectors (EC and IC) by line-fitting their respective data entries. From Figure 9, we observe that no evidence might hint at a relationship between the two characteristics. The fitted-line slope prediction is weak, the value of the adjusted coefficient of determination is very low (5%), while several datapoints are located out-of-bounds of the 95% confidence band. Therefore, we proceed to perform the simultaneous screening of both responses, the energy consumption, and the intervention costs. Empirically, from the main-effects graph screening of the IC response (Figure 10), we observe that the leading controlling factors that cause greater modulation are: FC2, FC5, FC8, FC9, and FC11. On the other hand, the active controlling factors, after the final EC screening (Section 3.1), were found to be: FC1, FC4, FC11, and F12. The independent EC and JR screening solutions share only two common controlling factors: (1) the automation for hot water and (2) the type of the heating system. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Term** & **Coef** & **SE Coef** & **\(t\)-Value** & **\(p\)-Value** & **VIF** \\ \hline
**Constant** & 192.0 & 11.9 & 16.20 & 0.000 & \\
**FC1** & \(-\)36.27 & 8.84 & \(-\)4.10 & 0.006 & 1.57 \\
**FC2** & \(-\)1.29 & 9.75 & \(-\)0.13 & 0.899 & 1.91 \\
**FC4** & \(-\)31.57 & 8.33 & \(-\)3.79 & 0.009 & 1.39 \\
**F9** & \(-\)13.91 & 9.30 & \(-\)1.50 & 0.185 & 1.74 \\
**FC11** & \(-\)24.55 & 8.40 & \(-\)2.92 & 0.027 & 1.42 \\
**F12** & 23.31 & 8.81 & 2.65 & 0.038 & 1.56 \\
**FC21** & 11.37 & 8.55 & 1.33 & 0.232 & 1.47 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Coefficients of regression analysis of EC (seven-factor strong group). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Term** & **Coef** & **SE Coef** & **\(t\)-Value** & **\(p\)-Value** & **VIF** \\ \hline
**Constant** & 193.16 & 8.70 & 22.20 & 0.000 & \\ \hline
**FC1** & \(-\)38.52 & 7.39 & \(-\)5.21 & 0.001 & 1.06 \\ \hline
**FC4** & \(-\)35.42 & 7.44 & \(-\)4.76 & 0.001 & 1.07 \\ FC11 & \(-\)31.15 & 7.39 & \(-\)4.21 & 0.002 & 1.06 \\
**F12** & 29.91 & 7.44 & 4.02 & 0.003 & 1.07 \\ \hline \hline \multicolumn{5}{c}{**Model Summary**} \\ \hline
**R2** & \(\mathbf{R^{2}}\) & \(\mathbf{R^{2}}\) **(adj)** & \(\mathbf{R^{2}}\) **(pred)** \\ \hline
**90.80\%** & \multicolumn{2}{c}{86.71\%} & \multicolumn{2}{c}{75.88\%} \\ \multicolumn{5}{c}{Regression Equation:} \\ \multicolumn{5}{c}{EC = 193.16 \(-\) 38.52 FC1 \(-\) 35.42 FC4 \(-\) 31.15 FC11 + 29.91 F12} \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Coefficients of the regression analysis of EC (four-factor confirmation). The only common factor to influence both responses appears to be FC11. We conclude that each response is influenced for the most part by a different group of effects. This could complicate matters toward a compromised synchronous screening solution. It appears that at least eight effects might be considered for the concurrent solution. Equivocally, the optimal adjustments for the FC11 are located on the opposite ends of the two responses. Perhaps, a rough prognostication may be that the FC11 might be auto-neutralized which may cause it to vanish after the joint screening effort. Instead, we opt to calibrate the two characteristics according to our proposed methodology (Section 2.1.2).