# Cyberbullying Analysis in Intercultural Educational Environments Using Binary Logistic Regressions
## 4 Results
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Cyberviciims**} & \multicolumn{6}{c}{**Cyberbullities**} \\ \multicolumn{2}{c}{**provesves**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} \\ \cline{2-11} \cline{2-11}  & **Judism** & **Christian** & **Islam** & **Buddhism** & **Taçism** & **Any Religion** & **Judism** & **Christian** & **Islam** & **Buddhism** & **Taçism** & **Any Religion** \\ \hline Granada & 0.10000 & 0.14736 & 1.5918 & 0.10000 & 0.10000 & 0.33653 & 1.0294 & 0.41463 & 0.43243 & 0.23041 & 0.71102 & 1.3618 \\ Midaga & 0.52800 & 0.44444 & 1.2121 & 0.45838 & 0.46808 & 1.9111 & 0.18885 & 0.00391 & 0.02985 & 0.02941 & 0.02985 & 0.03898 \\ Almeria & 0.48076 & 0.28577 & 1.4285 & 1.6500 & 0.72216 & 1.1428 & 0.41666 & 0.63366 & 0.63366 & 0.79310 & 0.76666 & 1.0526 \\ Jain & 0.16071 & 0.98651 & 0.72039 & 0.76474 & 0.76474 & 1.6457 & 1.3963 & 0.74074 & 0.72442 & 0.28497 & 0.78959 & 1.2727 \\ Cordoba & 0.55966 & 0.51612 & 2.5762 & 0.32913 & 0.32490 & 1.4285 & 3.3213 & 0.50241 & 0.79166 & 0.77368 & 0.08315 & 0.08974 \\ Servilla & 0.58333 & 0.51179 & 0.43434 & 0.97273 & 0.13369 & 2.0588 & 0.40144 & 0.52941 & 0.22222 & 0.22752 & 0.13334 & 1.3214 \\ Coldiz & 0.09200 & 0.13207 & 0.23611 & 0.13707 & 0.15384 & 0.13953 & 0.38811 & 0.35294 & 0.38253 & 0.18207 & 0.32857 & 2.2564 \\ Hueva & 0.26122 & 0.57971 & 0.53333 & 0.28231 & 1.26212 & 1.1428 & 0.44612 & 0.44242 & 0.28654 & 0.11740 & 1.5213 \\ Meilla & 0.57142 & 1.1571 & 1.1666 & 0.86206 & 0.89285 & 1.0811 & 2.2821 & 0.64814 & 1.1250 & 0.44594 & 0.73958 & 1.6071 \\ Cetus & 0.84902 & 0.13227 & 4.3333 & 0.29024 & 0.31945 & 0.38157 & 0.92500 & 0.80294 & 0.52272 & 0.4396 & 0.26151 & 2.22361 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Analysis of the Binary Logistic Regression showing the association between religion and the profile of cyberviciims and cyberbullities of the differentiated sample in provinces. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Cyberviciims**} & \multicolumn{6}{c}{**Cyberbullities**} \\ \multicolumn{2}{c}{**proves**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} \\ \cline{2-11} \multicolumn{1}{c}{**proves**} & \multicolumn{2}{c}{**Citypery**} & \multicolumn{2}{c}{**Citicitic**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} & \multicolumn{2}{c}{**aOR**} \\ \hline Granada & 3.0099 & 0.21028 & 0.241488 & 0.65625 & 5.4666 & 0.40476 & 0.71102 & 1.28877 \\ Malaga & 0.48833 & 0.45833 & 0.73060 & 0.55055 & 0.02941 & 0.02985 & 0.00270 & 0.00903 \\ Almeria & 1.7047 & 1.1026 & 1.6500 & 1.0416 & 0.40078 & 0.76666 & 0.79310 & 2.0132 \\ Jain & 1.3225 & 0.76744 & 1.2079 & 0.41666 & 1.1176 & 0.28497 & 0.78959 & 1.8997 \\ Cordoba & 1.5641 & 1.6153 & 1.2459 & 2.3148 & 3.2063 & 0.07368 & 0.06451 & 0.07526 \\ Sevilla & 0.76135 & 1.8545 & 1.5526 & 1.1818 & 2.3235 & 0.22784 & 0.70688 & 2.0285 \\ Cadiz & 0.15384 & 0.16981 & 0.82142 & 0.08076 & 3.2857 & 0.31914 & 0.45684 & 0.60816 \\ Houeva & 3.3461 & 0.28231 & 0.51612 & 0.97837 & 0.24324 & 0.11452 & 0.23684 & 0.99999 \\ Mellia & 0.87719 & 0.59057 & 0.14685 & 0.52758 & 0.48533 & 0.44594 & 0.43205 & 0.29910 \\ Cetus & 4.1142 & 0.84902 & 0.37209 & 0.22222 & 0.44230 & 0.28651 & 0.42592 & 0.31168 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Analysis of the Binary Logistic Regression showing the association between ethnicities and the profile of cyberviciims and cyberbullities of the differentiated sample in provinces. The analyses reveal that the gypsy ethnic group presents higher rates of probability for the acquisition of the role of cybervictim in the provinces of Granada (aOR 3.0909; 95% CI 12.9-2.8), Almeria (aOR 1.7047; 95% CI 0.8-0.7), Jaen (aOR 1.3225; 95% CI 0.9-1.7), Huelva (aOR 3.3461; 95% CI 0.9-12.7), Melilla (aOR.87719 95% CI 0.2-1.7), and Cetta (aOR 4.1142; 95% CI 0.8-18.7).