## 3 Application and Results
### Pre-Processing for Data Analysis  
The collected data show the change in the revenue water ratio and the leakage ratio according to the activity of leakage management (PR, LR, LD, MR). To evaluate the leakage reduction factors, these data were pre-processed. Table 2 shows the correlation between independent variables. Because the correlation depends on the data categorization, in this study, to compare the correlation by data classification criteria, revenue water ratio increase has been divided into four sections: (1) less than 60%, (2) 60-70%, (3) 70-80%, (4) higher than 80%, and four sections of leakage ratio: (1) less than 10%, (2) 10-20%, (3) 20-30%, (4) higher than 30%. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Study Area**} & **Revenue** & **Increase** & **Leakage** & **Deccase** & **Pipe** & **Meter** & **Leakage Repair** & **Leakage** \\  & **Water Ratio** & **Revenue** & **Ratio** & **Leakage** & **Replacement** & **Replacement** & **(LR)** & **Detection** \\ \cline{2-8}  & **\%** & **\%** & **\%** & **Ratio** & **(PR)** & **(MR)** & **(MR)** & **(LD)** \\ \cline{2-8}  & **\%** & **\%** & **\%** & **\%** & **km/km \(\times\) Million** & **No./Per. \(\times\) 1000** & **No./km \(\times\) 1000** & **No./km \(\times\) 1000** \\ \hline GeS 2009 & 69.5 & \(-1.1\) & 25.1 & \(-1.0\) & 32.920 & 23.754 & 0.905 & 0.237 \\ \hline NS 2007 & 69.8 & 5.3 & 27.5 & 1.9 & 125.818 & 10.432 & 2.604 & 0.074 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Standard of**} & **PR** & **MR** & **LR** & **LD** \\ \hline \multirow{8}{*}{All data} & \multirow{8}{*}{Leakage ratio of higher than 20\%} & PR & 1 & - & - & - \\ \cline{3-6}  & & MR & \(-0.103\) & 1 & - & - \\ \cline{3-6}  & & LR & 0.401 & \(-0.145\) & 1 & - \\ \cline{3-6}  & & LD & 0.006 & \(-0.044\) & 0.360 & 1 \\ \cline{3-6}  & & PR & \(1\) & - & - & - \\ \cline{3-6}  & & PR & \(1\) & - & - & - \\ \cline{3-6}  & & PR & \(1\) & - & - & - \\ \cline{3-6}  & & PR & \(1\) & - & - & - \\ \cline{3-6}  & & LR & 0.832 & 0.422 & 1 & - \\ \cline{3-6}  & & LD & 0.854 & 0.457 & 0.866 & 1 \\ \hline \hline \multirow{8}{*}{The leakage ratio} & \multirow{8}{*}{10–20\%} & PR & 1 & - & - & - \\ \cline{3-6}  & & PR & 1 & - & - & - \\ \cline{3-6}  & & MR & 0.021 & 1 & - & - \\ \cline{3-6}  & & LR & 0.416 & \(-0.002\) & 1 & - \\ \cline{3-6}  & & LD & 0.272 & 0.064 & 0.649 & 1 \\ \cline{3-6}  & & PR & 1 As a result, PR-LR (0.832), PR-LD (0.854), and LD-LR (0.866) of leakage ratio less than 10% showed a high correlation of more than 0.7. Therefore, the leakage ratio of less than 10% data was excluded when generating the prediction equation. In addition, the data with a revenue water ratio of less than 60% showed a high correlation for LD-PR (0.71), but in other data show correlation of less than 0.7. Moreover, in order to minimize the problem of collinearity between independent variables, there should be no correlation between independent variables. However, the correlation between the dependent and independent variables should be high. Therefore, this study performed an analysis of correlation between the independent and the dependent variable, and Table 3 shows the results. Table 3 shows the results of analysis of correlation components between dependent-independent variables according to various classification criteria. Only data of the leakage ratio of less than 10% showed high correlation between dependent-independent variables, and low correlation in other cases. In other words, it was confirmed that, even if old pipes and meters were replaced and leakage detection and repair were performed in some areas, the tendency of a large increase in the revenue water ratio or a decrease in the leakage ratio was small. For this reason, in order to derive a leakage management formulation according to the data analysis group, it is necessary to include significant independent variables and remove statistically insignificant independent variables.