# Analyzing Port State Control Data to Explore Future Improvements to GMDSS Training
## 3 Results
### Examining the Independence of Subset HRSC2 and HRSC3  
Now consider the Chi-square tests in which the null hypothesis is that no relationship exists between the categorical variables in both subsets (HRSC2 and HRSC3), so they are independent. The results of the \"Pearson Chi-Square\" \(\chi(3)=25,459,p<0.001\), indicate there is not any statistically significant association between the distribution of the independent variable \"country flags\" between the subsets HRSC2 and HRSC3. Again, Pearson Chi-Square\" \(\chi(3)=27,173,p<0.001\) indicates that there is not any statistically significant association between the independent variable distribution \"ship-type\" between the subsets HRSC2 and HRSC3. Concerning the category \"port situation\", the results of the \"Pearson  
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline \multirow{2}{*}{**Subsets Description**} & **Cut-Off Criterion** & **Number of Vessels** & **Percentage** & **Number of Vessels** & **Percentage** & **Number of Vailures within the Total of Cut-Off Criterion** & **Percentage** & **Number of Failures within the Cott-Off Criterion** & **Percentage** & **Considering the Total of Deficiencies (Q3,911)** \\ \hline HRSC1. Based on the number of inspections with deficiencies & 4 inspections in period or more & (31.4 years) & 1297 (31.4 years) & 9.8\% & 6616 & 27.9\% & 8992 & 29.1\% \\ HRSC4. Based on the number of deficiencies of the number of deficiencies & 5 deficiencies or more & (30.3 years) & 11.8\% & 6894 & 29.1\% & 10,949 & 35.4\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of subsets classified as “High Risk” following different criteria, HRSC1 vs. HRSC4.  
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline \multirow{2}{*}{**Subsets Description**} & \(-2\)**Log Likelihood** & **Nagelkerke Pseudo** & **Sensitivity of the Model** & **Specificity of the Model** & **Overall Relation** & **Predicted/Observed of the Model** & **Model** \\ \hline HRSC1. Based on the number of inspections with deficiencies & 22,712 & 0.292 & Correctly classify the 43.5\% of High-Risk cases & Correctly classify the 89.5\% of Moderate Risk cases. & 76.7\% improving the intercept-only model \\ HRSC4. Based on the number of deficiencies & 34,365 & 0.236 & Correctly classify the 46.1\% of High-Risk cases & Correctly classify the 84.6\% Moderate Risk cases & 71\% improving the intercept-only model \\ \hline \hline \end{tabular}
\end{table}
Table 7: Results of comparison between binary logistic results applied to both subsets.  
Chi-Square\" x(3) = 594, \(p<0.001\), indicate there is not any statistically significant association between the distribution of the independent variable \"port situation\" between the subsets HRSC2 and HRSC3. Therefore, the null hypothesis can be rejected and we can conclude that there are statistically significant differences between the data proportions of both subsets, HRSC2 and HRSC3, regarding the three categorical explanatory variables revised.  
When examining the distribution of the continuous variable ship age (Figure 1), [PERSON]'s Test for Equality of Variances shows there are significant differences between the variances of both sub-groups. Even so, the study found that HRSC3 had a statistically significantly lower age of 26.7 years compared with HRSC2, with a higher age mean of 28.4 years with t(4084.987) = \(-\)5.911, \(p<0.001\).  
In these circumstances (violating the normality of data and equality of variances), the alternative non-parametric test has been applied, which shows the same results. The mean rank and sum of ranks for the two groups tested show that the HRSC2 subset has ships with higher ages. Facing the results of the Mann-Whitney U test of independent variable ship-age of both distributions (HRSC2 vs. HRSC3) subsets, it can be concluded that there were statistically significant differences between both subsets (U = 3,898,401; \(p=0.014\)).