## 3 Results
### Preprocessing
#### 3.1.3 Analysis of Variance
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Variables** & **In** & **Out** & **Boundary** & **F-Value** & **\(p\)-Value** & **Variables** & **In** & **Out** & **Boundary** & **F-Value** & **\(p\)-Value** \\ \hline Complex & 1533 \({}^{\text{A}}\) & 708 \({}^{\text{B}}\) & 73 \({}^{\text{C}}\) & 33.84 & \textless{}0.001 & Iso-butyric acid & 36.23 \({}^{\text{A}}\) & 17.96 \({}^{\text{A}}\) & 2.01 \({}^{\text{B}}\) & 33.16 & \textless{}0.001 \\ Ammonia & 5.74 \({}^{\text{A}}\) & 2.54 \({}^{\text{B}}\) & 0.49 \({}^{\text{C}}\) & 38.52 & \textless{}0.001 & Butricy acid & 323.15 \({}^{\text{A}}\) & 173.78 \({}^{\text{B}}\) & 11.95 \({}^{\text{C}}\) & 30.48 & \textless{}0.001 \\ Hydrogen sulfide & 357.28 \({}^{\text{A}}\) & 275.63 \({}^{\text{A}}\) & 16.27 \({}^{\text{B}}\) & 16.95 & \textless{}0.001 & Iso-valeric acid & 95.74 \({}^{\text{A}}\) & 48.04 \({}^{\text{B}}\) & 4.81 \({}^{\text{C}}\) & 23.63 & \textless{}0.001 \\ Methyl & 14.26 \({}^{\text{A}}\) & 4.24 \({}^{\text{B}}\) & 1.18 \({}^{\text{B}}\) & 13.90 & \textless{}0.001 & Valeric acid & 186.40 \({}^{\text{A}}\) & 85.17 \({}^{\text{B}}\) & 6.81 \({}^{\text{C}}\) & 16.31 & \textless{}0.001 \\ Dimethyl & 11.87 & 6.08 & 0.11 & 1.40 & 0.2501 & Phenol & 12.66 \({}^{\text{A}}\) & 6.28 \({}^{\text{B}}\) & 2.60 \({}^{\text{B}}\) & 11.40 & \textless{}0.001 \\ Dimethyl disulfide & 0.20 & 0.13 & 0.06 & 1.82 & 0.1639 & p-Cresol & 69.12 \({}^{\text{A}}\) & 36.60 \({}^{\text{B}}\) & 3.38 \({}^{\text{C}}\) & 24.49 & \textless{}0.001 \\ Acetic acid & 495.79 \({}^{\text{A}}\) & 218.76 \({}^{\text{A}}\) & 45.75 \({}^{\text{C}}\) & 25.48 & \textless{}0.001 & Indole & 2.45 & 1.82 & 2.36 & 0.16 & 0.8489 \\ Propionic Acid & 380.37 \({}^{\text{A}}\) & 177.05 \({}^{\text{B}}\) & 21.23 \({}^{\text{C}}\) & 33.91 & \textless{}0.001 & Skatole & 4.35 & 2.28 & 3.13 & 0.85 & 0.4309 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Analysis of variance results for location. The subscripts (\({}^{\text{A}}\), \({}^{\text{B}}\), \({}^{\text{C}}\)) above the numbers grouped the mean of each category in the case of variables with significant differences in mean. Figure 5: Number of counts for location and season. As Table 7 shows, no differences were observed in the average amount of occurrence per season across seven variables (complex odor, NH\({}_{3}\), H\({}_{2}\)S, DMDS, p-C, ID, and SK) for the measurement time variable (season). For the nine variables excluding these, the average generation differed by season (\(p\)-value \(<\) 0.05). Regarding the average occurrence amount by season, a difference was observed only in the spring for DMS, ACA, PPA, BTA, and IVA. In all cases, the average occurrence was highest in the spring. VLA showed a difference in the average occurrence only in the fall, during which the amount was the lowest. For MM, the difference in the average occurrence amount was significant in summer and fall, and the average occurrence amount was the largest in summer. Finally, for IBA and Ph, the difference in average occurrence was significant only in spring and fall, and the average occurrence amount was the largest in spring. As such, for both location and season, the difference in average occurrence by category was found to be significant for most variables. These can be considered suitable for use as variables.