## 5 Research Results and Discussion
### Model for Estimating the Total Daily Number of Visitors and Vehicles in the Shopping Centre Zone
The previously described Backward Elimination procedure, to estimate the total daily number of visitors in the shopping centre zone (UBO), formed five models whose summary results are shown in Table 4. For each model, the correlation value--R, the coefficient of determination--R Square, the adjusted coefficient of determination--Adjusted R Square and the standard error--Std. Error of the Estimate. Taking into account the values of the above-mentioned model quality indicators, it is concluded that Model 1 with all five independent variables shows the best agreement with the actual data (R Square = 0.973). The results of the analysis of variance (ANOVA) for the five UBO assessment models are shown in Table 5. The realised significance of the _Sig_. test statistics indicates that only linear models 3, 4 and 5 have statistically significant differences in independent effects on the dependent variable. The specific values of the regression coefficients figuring in the models--Unstandardized Coefficients B are given in Table 6, and the statistical significance of each of them is represented by the value of the Sig. \(t\) test. It can be observed that the constant (Sig. = 0.023) and the coefficient with the UPP Model 5 variable (Sig. = 0.006) are the only statistically significant coefficients. The formed models for the estimation of the UBO (total number of persons in the vehicle on arrival--both driver and passengers) can be mathematically recorded in the manner presented in Table 7. \begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Model**} & **Independent** & \multirow{2}{*}{**R**} & \multirow{2}{*}{**Square**} & **Adjusted R** & **Std. Error of the** \\  & **Variables/Predictors** & & & **Square** & **Estimate** \\ \hline
1. & BPM, BD, UPP, BRPV, BS & 0.986 & 0.973 & 0.838 & 664.377 \\
2. & BD, UPP, BRPV, BS & 0.983 & 0.966 & 0.897 & 529.279 \\
3 & BD, UPP, BS & 0.972 & 0.946 & 0.891 & 544.736 \\
4 & BD, UPP & 0.934 & 0.872 & 0.808 & 722.491 \\
5 & UPP & 0.895 & 0.801 & 0.761 & 806.336 \\ \hline \end{tabular}
\end{table} 
Table 4: Linear models for UBO estimation—summary results. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**Unstandardized Coefficients**} & \multicolumn{2}{c}{**Standardized Coefficients**} & \multirow{2}{*}{**T**} & \multirow{2}{*}{**Sig.**} \\ \cline{3-4} \cline{6-7}  & & **B** & **Std. Error** & & **Beta** & \\ \hline \multirow{4}{*}{1.} & Constant. & 791.404 & 899.357 & & 0.880 & 0.541 \\  & BS & \(-\)0.138 & 0.072 & \(-\)5.206 & \(-\)1.920 & 0.306 \\  & BD & 0.457 & 0.226 & 6.097 & 2.207 & 0.292 \\  & BRPV & \(-\)0.128 & 0.127 & \(-\)1.819 & \(-\)1.004 & 0.499 \\  & UPP & 0.337 & 0.171 & 1.925 & 1.970 & 0.299 \\  & BPM & 1.368 & 2.636 & 0.211 & 0.519 & 0.695 \\ \hline \multirow{4}{*}{2.} & Constant. & 1109.700 & 524.016 & & 2.118 & 0.168 \\  & BS & \(-\)0.130 & 0.056 & \(-\)4.891 & \(-\)2.323 & 0.146 \\  & BD & 0.410 & 0.164 & 5.466 & 2.494 & 0.130 \\  & BRPV & \(-\)0.088 & 0.081 & \(-\)1.261 & \(-\)1.085 & 0.391 \\  & UPP & 0.319 & 0.134 & 1.824 & 2.391 & 0.139 \\ \hline \multirow{4}{*}{3} & Constant. & 1300.942 & 507.910 & & 2.561 & 0.083 \\  & BS & \(-\)0.107 & 0.053 & \(-\)4.039 & \(-\)2.009 & 138 \\  & BD & 0.301 & 0.134 & 4.015 & 2.247 & 0.110 \\  & UPP & 0.191 & 0.063 & 1.090 & 3.012 & 0.057 \\ \hline \multirow{4}{*}{4} & Constant. & 1367.230 & 672.225 & & 2.034 & 0.112 \\  & BD & 0.034 & 0.023 & 0.454 & 1.493 & 210 \\  & UPP & 0.092 & 0.053 & 0.528 & 1.734 & 0.158 \\ \hline \multirow{4}{*}{5} & Constant. & 1963.657 & 603.301 & & 3.255 & 0.023 \\  & UPP & 0.157 & 0.035 & 0.895 & 4.486 & 0.006 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Linear model coefficients for UBO estimation.