Research on relationships between variation in ²²²Rn activity concentration and tectonic events recorded using the instruments of the Geodynamic Laboratory of SRC PAS at Książ (the Sudetes, SW Poland) had been conducted since 2014. The performed analyses of variation have demonstrated the spatial character of changes in ²²²Rn activity concentration. Their time-course is comparable in all parts of the underground laboratory. This means that gas exchange between the lithosphere and the atmosphere occurs not only through fault zones but also through all surfaces of the underground workings: the floors, the sidewalls and the roofs. Further, some relationships between ²²²Rn activity concentration and tectonic activity of the orogen have been demonstrated with the use of Pearson's linear correlation coefficient. The comparison between temporal distribution (times series) of radon activity concentration and water-tube tiltmeters (WTs) demonstrated that radon data have regular oscillations which can be approximated using the sine function with a 12 month cycle (seasonal changes) and amplitude in the range of 1000–1500 Bq/m³. To compare the collected radon signal data and tectonic activity, we used linear function as the simplest method of trend assessment. Pearson's correlation coefficient r cannot be accepted as appropriate for assessing the interdependencies between variables because they do not have a normal distribution, and the relationship between them is not linear.

It was noted that each series of data, namely radon activity concentration and tectonic activity determine the series of deviations above and below the trend function. Because of the non-fulfillment of the above assumptions, we used nonparametric equivalents such as Spearman's rank correlation coefficient r_s and Kendall's tau. The obtained results showed that the value of the r_s coefficient ranges from 0.38 to even 0.43. The best relationship at the level of r_s = 0.43 was determined between the radon activity concentration recorded by detector no. 3 and the tectonic activity of the rock mass registered on the WT-2 channel. Similar at the r_s level of 0.37–0.38 between detector no. 5 and 4 and the WT-2 channel. A bit higher than r_s = 0.39 between detector no. 3 and the WT-2 channel. In each case, these were positive correlations. The obtained Spearman's r_s coefficients indicate the correlation between ²²²Rn activity concentration and tectonic activity of the rock mass. The t-statistic, which analyzes the significance of Spearman's coefficient r_s is a descriptive measure of the accuracy of regression matching to empirical data. It takes values in the range of percentage and provides informations about which part of the total variability of the radon activity concentration (Y) observed in the sample has been explained (determined) by regression in relation to tectonic activity of the rock mass (X). In our case, approximately f 40% to more than 50% of the radon activity concentration (Y) was explained by regression in relation to the tectonic activity of the rock mass. We obtained similar results with the use of Kendall's tau coefficient.

Precise description of the character of this relationship requires further, more detailed analyses, such as comparing characteristics of the distributions based on trend variation like Monte Carlo simulation, Multivariate Adaptive Regression Splines or neural networks.

自2014年以来，使用Ssi PAS地球动力学实验室的仪器在Książ（波兰Sudetes，SW）进行了²²² Rn活度浓度变化与构造事件之间关系的研究。²²² Rn活性浓度的变化。他们的时间过程在地下实验室的所有部分都是可比的。这意味着岩石圈与大气之间的气体交换不仅通过断层带发生，而且还通过地下工程的所有表面：地板，侧壁和屋顶进行。此外，²²²之间的一些关系利用皮尔森线性相关系数证明了造山带的Rn活度浓度和构造活动。ra活度浓度的时间分布（时间序列）与水管倾斜仪（WTs）之间的比较表明，ra气数据具有规则的振荡，可以使用正弦函数以12个月的周期（季节性变化）和幅度在该范围内进行近似1000-1500 Bq / m ³。为了比较收集的ra信号数据和构造活动，我们使用线性函数作为趋势评估的最简单方法。皮尔逊相关系数r由于变量不具有正态分布，并且变量之间的关系不是线性的，因此不能适当地用于评估变量之间的相互依赖性。

注意到，每个系列的数据，即ra活度浓度和构造活动，决定了趋势函数之上和之下的一系列偏差。由于上述假设不成立，我们使用了非参数等价物，例如Spearman秩相关系数r _s和Kendall tau。将所得到的结果表明，该值ř_小号系数的范围从0.38到0.43，甚至。 确定在r _s = 0.43的水平上的最佳关系是由探测器No.1记录的the活度浓度之间的关系。3和WT-2通道上记录的岩体的构造活动。在类似[R_小号探测器号之间的水平为0.37–0.38。5和4以及WT-2频道。 检测器编号之间的比r _s = 0.39高一点。3和WT-2频道。在每种情况下，这些都是正相关。获得的Spearman的r _s系数表明²²² Rn活度浓度与岩体的构造活动之间的相关性。所述吨t-统计，其分析斯皮尔曼系数的意义- [R_小号是对与经验数据匹配的回归准确性的描述性度量。它采用百分比范围内的值，并提供有关样品中观测到的activity活度浓度（Y）的总变化的哪一部分已通过与岩体（X）的构造活动有关的回归进行解释（确定）的信息。 。在我们的案例中，by的大约40％到50％以上的activity活度浓度（Y）通过岩体构造活动的回归来解释。使用肯德尔的tau系数，我们获得了相似的结果。

对这种关系的特征的精确描述需要进一步，更详细的分析，例如基于趋势变化（如蒙特卡洛模拟，多元自适应回归样条或神经网络）比较分布的特征。