# Noise Annoyance in Physical Sciences: Perspective 2015-2024
## 3 Results
Conversely, if the \(p\)-value significantly exceeds the assumed significance level, there would be no statistical basis to reject the null hypothesis, suggesting the absence of statistically significant differences in the distribution of the analyzed categories between the two time periods. However, to fully understand the statistical significance and the relationships presented, it is crucial to define the symbols used within the table, particularly the \(\chi^{2}\) symbol representing the chi-square statistic and df indicating the degrees of freedom. Additionally, clarifying what each category name (e.g., conference paper, renewable energy, experiment) represents within the context of this study is essential for accurate interpretation by the reader. After checking the chi-square coefficient value, only the document type category showed a \(p\)-value slightly higher than 0.05 (0.0518). The remaining categories are characterized by a significantly higher \(p\)-value than the assumed significance level. It should therefore be considered that there is no basis for rejecting the null hypothesis, which means that no statistically significant differences were detected. Figure 3 presents bar charts illustrating the number of document types published across two distinct timeframes: 2015-2019 and 2020-2024. This division was strategically chosen to highlight potential shifts in publication trends within the most recent decade of research on noise annoyance in physical sciences, allowing for an examination of the evolution of knowledge dissemination in this field. Regardless of the specific five-year period, journal articles consistently constituted the largest proportion of the analyzed publications, totaling 73 across both periods (65.18% of all analyzed works). Conference papers formed the second largest category with 30 publications (26.79% of the total). Book chapters represented the smallest group, with nine publications overall (8.04%). Notably, this general distribution pattern remained consistent across both analyzed timeframes. The most significant change was observed in the book chapter category, which saw eight publications in the 2015-2019 period but only one in 2020-2024. This trend warrants further investigation in the Discussion section. In this context, the limitation of the article should be noted. Conference materials are usually not peer-reviewed, which weakens their scientific value. The distribution of document types across these periods is visually represented in Figure 3. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Name** & **2015–2019** & **2020–2024** & **All Years** & **Share [\%]** & **Chi-Square** \\ \hline Total & 56 & 56 & 112 & 100.0 & 0.0 \\ \hline
**Document type** & & & & & \\ \hline Conference paper & 14 & 16 & 30 & 26.79 & \multirow{2}{*}{\(\chi^{2}=5.92\)} \\ Journal article & 34 & 39 & 73 & 65.18 & \\ Book chapter & 8 & 1 & 9 & 8.04 & \\ \hline
**Noise source** & & & & & \\ \hline Renewable energy & 10 & 6 & 16 & 14.29 & \multirow{2}{*}{\(\chi^{2}=0.476\)} \\ Air transport & 17 & 21 & 38 & 33.93 & \\ Rail transport & 6 & 7 & 13 & 11.61 & \\ Road transport & 32 & 25 & 57 & 50.89 & \\ Urban noise & 21 & 24 & 45 & 40.18 & \\ \hline
**Subject area** & & & & & \\ \hline Environmental science & 35 & 33 & 68 & 60.71 & \\ Engineering & 18 & 30 & 48 & 42.86 & \\ Energy & 8 & 7 & 15 & 13.39 & \\ Earth and planetary sciences & 6 & 3 & 9 & 8.04 & \\ \hline
**Research methodology** & & & & & \\ \hline Experiment & 32 & 41 & 73 & 65.18 & \\ Survey & 23 & 26 & 49 & 43.75 & \\ Literature analysis & 13 & 12 & 25 & 22.32 & \\ Case study & 10 & 6 & 16 & 14.29 & \\ Conceptual & 37 & 31 & 68 & 60.71 & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Quantitative summary of publications in 2015–2019 and 2020–2024 in all categories.