## 4 Results
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \(\begin{array}{c}\textbf{Statistical}\\ \textbf{Parameters}\end{array}\) & \begin{tabular}{c} **Sorrentina** \\ **Peninsula** \\ \end{tabular} & \begin{tabular}{c} **Massa** \\ **Lubrene** \\ \end{tabular} & \begin{tabular}{c} **Meta** \\ **Sorrento** \\ \end{tabular} & \begin{tabular}{c} **Piano di** \\ **Sorrento** \\ \end{tabular} & \begin{tabular}{c} **Sant\({}^{\prime}\)Agnello** \\ **Sorrento** \\ \end{tabular} & \
\begin{tabular}{c} **Sorrento** \\ **Equense** \\ \end{tabular} &
\begin{tabular}{c} **Vico** \\ **Equense** \\ \end{tabular} \\ \hline AM (Bq/m3) & 182 & 216 & 178 & 171 & 259 & 188 & 121 \\ \cline{2-7} SD (Bq/m3) & 162 & 259 & 115 & 154 & 219 & 149 & 49 \\ CV = SD/AM & 0.89 & 1.20 & 0.65 & 0.90 & 0.85 & 0.79 & 0.40 \\ GM (Bq/m3) & 139 & 152 & 152 & 130 & 187 & 144 & 108 \\ GSD (Bq/m3) & 1.36 & 1.40 & 1.29 & 1.37 & 1.45 & 1.39 & 1.27 \\ Min (Bq/m3) & 23 & 59 & 61 & 55 & 54 & 48 & 23 \\ Med (Bq/m3) & 135 & 129 & 156 & 151 & 139 & 154 & 123 \\ Max (Bq/m3) & 933 & 454 & 632 & 636 & 546 & 216 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Statistical parameters both for the total measurements on the Sorrentina peninsula and for each municipality after data normalization. Figure 4: (a) Log-normal distribution of the indoor radon concentration for each dwelling; (b) Q–norm plot of natural log-transformed radon concentration for each dwelling. Approximately 13% of the measurements made exceed the reference level of 300 Bq/m\({}^{3}\) established by the Italian Legislative Decree 101/2020, which transposes the European Directive on Fundamental Safety Standards (BSS)-2013/59 [9]. Soil is thought to be the primary source of indoor radon. Unfortunately, the study was unable to evaluate the relationship between radon concentrations and the geological features of the soil on which the structures were erected. A correlation study, however, was performed using the municipality as the soil's proxy variable. Figure 5 depicts a box plot of Rn concentration in Bq/m\({}^{3}\) by municipality. The analysis of variance (ANOVA) method was used to compare different groups (municipality). According to the findings, the municipality has no statistically significant effect on indoor radon levels. Regarding the study of the spatial autocorrelation of the measures, Figure 6 shows the Gini-based variogram that was obtained after the verification of the behavior of the classical variogram, which describes, in this specific case, a quasi-stationary model. The variogram has a discontinuity at the origin: \(\gamma(h)\) does not tend to zero when \(h\) tends to zero, but \(\gamma\left(0\right)>0\) is observed. A relevant nugget effect can be identified. The presence of the nugget effect is expected in cases of quantities relating to Rn [26; 27; 37]. In this example, the presence is due to measurements with a high level of error at short distances. Given the size of the investigated area, the amount of data supplied can be regarded to be sufficient for the study. The geostatistical analysis of the data shows that there is a geographical correlation; the variogram was represented by the following function:  
\[\gamma(h)=S\cdot\left[1-\exp\left(-\frac{h}{R}\right)^{\alpha}\right]+N \tag{6}\]  
where \(\alpha=1.5\)[14], the sill was 0.18, the range was 0.87 km, and the nugget was 0.33. The high value of the nugget effect confirms that the indoor radon concentration has a high variability at small spatial scales, as also shown by the measurements. Figure 5: Box plot of Rn concentration in Bq/m\({}^{3}\) by municipality. The continuous line denotes the median, the boxes enclose the quartiles, the dots represent the outliers. The variogram's trend was demonstrated at a distance of up to 5 km, for which spatial correlation was ensured. Beyond this distance, the variogram's behavior is indicative of a non-stationarity situation. In this framework, in the Gini-based approach the variogram was computed by clustering a larger number of experimental data.