## 3 Results and Discussion
### Statistical Analysis of Survey Results  
The survey results were statistically analysed. To compare the means of the two groups--odour annoyance and odour intensity--a paired sample \(t\)-test with 95.0% confidence interval was performed. The t-value is \(-10.11\), while the degrees of freedom is 787, [PERSON]'s d effect size is \(-0.717\), and \(p\)-value is \(<0.001\). The mean difference is \(-0.510\), while the standard error SE difference = 0.025. The alternative hypothesis was that the difference is not 0, so the null hypothesis was rejected of no difference; with a high degree of confidence, the true difference in means is not equal to zero (Figure 13). Table 4 contains descriptive statistics of odour annoyance and odour intensity (as dependent variables) and wind direction as a fixed factor, while Figure 14 contains descriptive plots of those parameters. In Figure 14, there are presented odour annoyance and odour intensity grouped by wind direction (abbreviations: SD--standard deviation, N--number of observations). To verify whether there are statistically significant differences between the mean values of odour intensity and odour annoyance, with wind direction as a fixed factor, the ANOVA \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{4}{c}{**Descriptives—Odour Annoyance**} \\ \hline
**Wind Direction** & **Mean** & **SD** & **N** \\ \hline E & 3.872 & 0.801 & 39 \\ N & 4.065 & 0.744 & 155 \\ NE & 4.196 & 0.720 & 107 \\ NW & 4.039 & 0.717 & 127 \\ S & 4.000 & 0.763 & 56 \\ SE & 4.211 & 0.674 & 71 \\ SW & 4.250 & 0.670 & 40 \\ W & 4.060 & 0.712 & 50 \\ \hline \hline \multicolumn{4}{c}{**Descriptives—Odour Intensity**} \\ \hline
**Wind direction** & **Mean** & **SD** & **N** \\ \hline E & 4.462 & 1.211 & 39 \\ N & 4.613 & 1.034 & 155 \\ NE & 4.748 & 1.150 & 107 \\ NW & 4.409 & 1.042 & 127 \\ S & 4.321 & 1.011 & 56 \\ SE & 4.746 & 1.092 & 71 \\ SW & 5.025 & 0.733 & 40 \\ W & 4.580 & 0.992 & 50 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Descriptive statistics of odour annoyance and intensity with wind direction as a fixed factor. Figure 14: Descriptive plots of odour annoyance and intensity with wind direction as a fixed factor. test was used. The results of the ANOVA tests for odour intensity with wind direction as a fixed factor are the following:  
* No homogeneity correction: F factor = 2.684, \(p\) = 0.010, size of effect: \(\eta^{2}\) = 0.029, \(\varpi^{2}\) = 0.018;
* Brown-Forsythe homogeneity correction: F factor = 2.752, \(p\) = 0.008, size of effect: \(\eta^{2}\) = 0.029, \(\varpi^{2}\) = 0.018;
* Welch homogeneity correction: F factor = 3.544, \(p\) = 0.001, size of effect: \(\eta^{2}\) = 0.029, \(\varpi^{2}\) = 0.018. The results of the ANOVA tests for odour annoyance with wind direction as a fixed factor are the following:  
* No homogeneity correction: F factor = 1.643, \(p\) = 0.121, size of effect: \(\eta^{2}\) = 0.018, \(\varpi^{2}\) = 0.007;
* Brown-Forsythe homogeneity correction: F factor = 1.640, \(p\) = 0.122, size of effect: \(\eta^{2}\) = 0.018, \(\varpi^{2}\) = 0.007;
* Welch homogeneity correction: F factor = 1.597, \(p\) = 0.138, size of effect: \(\eta^{2}\) = 0.018, \(\varpi^{2}\) = 0.007. For odour annoyance, a one-factor analysis of variance showed no statistically significant differences between group means. On the other hand, the one-factor analysis of variance showed statistically significant differences between group means for odour intensity (F (7.00) = 2.68, \(p\) = 0.01, size of effect: \(\eta^{2}\) = 0.029, \(\varpi^{2}\) = 0.018). This means that at least one average is statistically significantly different from the others. To determine which is the average, post hoc tests were performed. Since the significance of the Levene variance non-homogeneity test was less than 0.05 (\(p\) = 0.003), variances were considered heterogeneous, i.e., differences between variances in the compared groups. Due to the lack of homogeneity of variance, the Dumnett test and the Games-Howell test were chosen.