## 3 Results and Discussion
### Statistical Analysis
This is due to the fact that these parameters are the main parameters in the process of forming a radon field. This conclusion was made in the conditions of the experiment and does not take into account other physical factors that can affect the behavior (gas permeability, humidity, temperature, pressure). The same parameters are involved in calculating the level of radon production. The second factor, with a dispersion of 21.15%, combines two parameters--true density and porosity. The relationship between these parameters is due to the fact that the porosity is a calculated value and is determined based on the density of the sample. The third factor is represented by one parameter--the activity of radionuclide \({}^{226}\)Ra. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multicolumn{3}{c}{**Factor**} \\ \cline{2-4}  & **1** & **2** & **3** \\ \hline A\({}_{\text{Ra}226}\) & \(-\)0.040 & 0.036 & 0.990 \\ K\({}_{\text{emanation}}\) & 0.876 & 0.271 & \(-\)0.256 \\ A\({}_{\text{Rn}222}\) & 0.776 & 0.288 & 0.418 \\ AV\({}_{\text{dens}}\) & \(-\)0.920 & 0.248 & 0.028 \\ TR\({}_{\text{dens}}\) & 0.071 & 0.992 & 0.054 \\ Porosity & 0.774 & 0.572 & 0.036 \\ \% of Variance & 52.81 & 21.15 & 17.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Factor loadings matrix for dataset on the studied parameters of radon emanation. The weak determination of the second and third factors is probably associated with more complex interaction mechanisms during the formation of the radon field; to fully understand them, additional data are required to determine the geochemical and mineralogical compositions [14]. Based on the results of measuring the volumetric activity of radon in a sealed container and calculating the level of radon production, we built a regression model (Figure 7), which is a linear function of the dependence of two parameters (dependent variable and regressor) and is characterized by regression coefficients (i.e., slope, coefficient of determination). In our experiment, the regression model has the form y = 19.138x \(-\) 32.696 and is characterized by a positive slope equal to 19.138 and a coefficient of determination R\({}^{2}\) = 0.8786. The positive slope indicates that with an increase in the level of radon production by 1 unit, the volumetric activity increases by 19.138 Bq\(\cdot\)m\({}^{-3}\). This value is theoretical and can vary depending on a number of parameters. For this model, it is calculated based on the results of the measurements of parameters. The value of the constant a = \(-\)32.696 in this case is not taken into account, because under ideal conditions (for example, the absence of extraneous sources of radon) at a level of radon production P = 0 Bq\(\cdot\)m\({}^{-3}\) h\({}^{-1}\), the volumetric activity will also be equal to 0 Bq\(\cdot\)m\({}^{-3}\). The coefficient of determination shows that the change in the volumetric activity of radon in the container (dependent variable) by 87.9% is described by the independent variable (regressor)--the level of radon production--which indicates a sufficient justification for choosing this model. This model more clearly predicts the distribution of radon based on the results of calculating the radon production rate. Figure 6: Plot of factor loadings for studied parameters of radon emanation.