## 4 Results
### Risk Coupling Value Test in the Two Accident Categories  
To explore whether there are significant differences in risk coupling values between the two ACs, the Wilcoxon signed-rank test was applied to the risk coupling values. The test examined the two hypotheses, H0 and H1, presented in the previous section. The result is shown in Table 6, where the statistic represents the cumulative extent of the positive or negative differences between the two sets of risk coupling values; \(Z\) indicates the extent to which the observed test statistic deviated from the expected value under the null hypothesis, with the sign indicating the direction of the difference and the absolute value reflecting the significance of the deviation; and the \(p\)-value represents the probability of observing the test statistic under the assumption that the null hypothesis (H0) is true. If the \(p\)-value in the test was less than 0.05, H0 was rejected; otherwise, it was not.  
According to Table 6, the \(p\)-value for the comparison between PA and SA was 0.0292, which was below the commonly used significance level of 0.05. This indicates that there was a statistically significant difference between the risk coupling values of PA and SA, meaning that the observed difference was unlikely to be due to chance. Furthermore, the z-value of \(-2.1588\) further confirmed this finding, with a negative value indicating that the risk coupling values in SA were significantly higher than those in PA. This result supports the hypothesis that the risk coupling mechanisms are distinct between PA and SA. Specifically, the stronger coupling in SA suggests a higher level of complexity and interaction among risk factors as the accident evolves. This difference is likely due to SA incorporating additional risk factors that accumulate and interact with those already present in PA, leading to stronger coupling effects. Moreover, while PA tend to be more isolated events, SA involve multiple stages of development, introducing dynamic changes and new risk factors over time. These evolving interactions significantly increase the overall risk coupling values in SA. Thus, the statistical significance of the findings strengthens the conclusion that the risk coupling mechanisms in PA and SA are fundamentally different, which is critical for developing targeted risk mitigation strategies for both types of accidents.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Group** & **AC** & **Q1** & **Medium** & **Q3** & **Statistic** & **Z** & \(p\)**-Value** & **Hypothesis Accepted** \\ \hline PA-SA & PA & 0.0049 & 0.0279 & 0.0966 & & & & \\ SA & SA & 0.0118 & 0.0391 & 0.0930 & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Wilcoxon signed-rank test results for risk coupling values in the two accident categories.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Rank** & **Coupling Scenario** & **Coupling Value** & **Coupling Scenario** & **Coupling Value** \\ \hline \multicolumn{5}{c}{PA} & SA \\ \hline
1 & \(T_{5}(H,V,R,W,M)\) & 0.096555 & \(T_{4,1}(H,V,R,W)\) & 0.155031 \\
2 & \(T_{4,1}(H,V,R,W)\) & 0.093765 & \(T_{4,5}(V,R,W,M)\) & 0.151980 \\
3 & \(T_{4