## 4 Discussions  
### Comparative Analysis of Subjective and Objective Evaluation Methods  
The mean objective score was slightly higher than the mean subjective score, as shown in Table 4. Both scoring methods demonstrated relatively low SDs, indicating that the scores were consistent across participants. However, the higher SD in objective scores suggests greater variability in objective measurements compared to subjective evaluations. This variability may reflect the objective method's sensitivity in capturing nuanced differences in device performance that subjective evaluations might overlook. To gain deeper insights into the discrepancies between subjective and objective scores, the differences (subjective score minus objective score) were calculated for each participant, as shown in Table 5. The mean difference was \(-3.18\) with an SD of 2.91, suggesting that subjective scores were generally lower than objective scores. The SD of 2.91 indicates moderate variability in these differences, highlighting that while the overall trend is consistent, individual participants exhibited varying degrees of discrepancy between the two scoring methods. A  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline  & \(S_{1}\) & \(S_{2}\) & \(S_{3}\) & \(S_{4}\) & \(S_{5}\) & \(S_{6}\) & \(S_{7}\) & \(S_{8}\) & \(S_{9}\) & \(S_{10}\) \\ \hline \(w_{i}\) & 0.0200 & 0.0112 & 0.0785 & **0.2440** & **0.1736** & **0.1613** & **0.1323** & 0.0175 & 0.0223 & **0.1394** \\ \hline \end{tabular}
\end{table}
Table 6: Entropy weights of objective indicators.  
Figure 6: Scatter plot of subjective scores and objective scores with regression line. Each point represents a participant’s scores. The positive slope of the regression line illustrates the positive correlation between the two scoring methods.  
Shapiro-Wilk test confirmed that the differences were normally distributed (\(p=0.1186\)), validating the use of parametric tests. The paired samples \(t\)-test revealed a statistically significant difference between subjective and objective scores (t(9) = \(-3.31\), \(p=0.0073\)), with a [PERSON]'s d value of \(-1.09\), indicating a large effect size and emphasizing the practical significance of this difference. Subjective evaluations are inherently influenced by personal biases, perceptions, and varying standards among evaluators [45]. In contrast, the objective method, enhanced by the entropy weight technique, provides a more standardized and quantifiable evaluation [39; 40].  
In Figure 5, the box plots illustrate the distribution of subjective and objective scores. The objective scores exhibited a higher median compared to the subjective scores, and the broader interquartile range (IQR) in objective scores indicates greater variability in evaluations. This suggests that the objective method is more sensitive to a wider range of performance aspects. The absence of outliers in the subjective scores indicates a relatively consistent evaluation across participants, suggesting that subjective evaluations were uniform in their scoring criteria. However, an outlier was identified in the objective scores for participant 9, who received a notably lower score of 64.2479. Furthermore, the box plot of the differences between subjective and objective scores (Figure 5) shows a median difference of \(-3.7566\) and an IQR of 3.1777, reflecting the spread of the central 50% of the differences. An outlier was detected for participant 9, who had a positive difference of 3.5021, indicating that their subjective score exceeded their objective score. The outliers in the box plots highlight a unique case where the subjective evaluation assigned a higher score compared to the objective method, suggesting that the objective evaluation method may detect specific deficiencies or unique performance traits not captured by subjective evaluations, potentially due to personal biases or unmeasured factors [45].