## 3 Data Introduction
### Analysis of Raw Data Characteristics
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Element** & **Region** & **Number** & **Min** & **25\%** & **50\%** & **75\%** & **Max** & **StdDev** & **Mean** & **Kurt** & **Skew** & **Coefficient** \\ \hline \multirow{3}{*}{Ag} & North & 3826 & 0.06 & 0.08 & 0.08 & 0.10 & 10.00 & 0.27 & 0.11 & 764.08 & 25.76 & 2.45 \\  & South & 6924 & 0.01 & 0.05 & 0.07 & 0.09 & 10.00 & 0.39 & 0.10 & 440.13 & 19.67 & 3.90 \\  & North & 3826 & 8.00 & 11.60 & 13.70 & 18.40 & 1000.00 & 24.02 & 17.47 & 1098.73 & 30.01 & 1.37 \\  & South & 6924 & 1.68 & 15.46 & 20.68 & 24.26 & 22,510.00 & 355.92 & 29.70 & 3276.66 & 56.01 & 11.98 \\  & North & 3826 & 7.70 & 13.80 & 16.30 & 19.10 & 669.90 & 20.53 & 18.38 & 422.47 & 18.34 & 1.12 \\  & South & 6924 & 1.33 & 17.38 & 19.43 & 21.94 & 1261.00 & 31.60 & 21.93 & 613.49 & 21.58 & 1.44 \\  & North & 3826 & 39.60 & 44.50 & 48.90 & 60.40 & 1000.00 & 51.97 & 61.41 & 112.64 & 8.90 & 0.85 \\  & South & 6924 & 2.37 & 46.92 & 55.98 & 65.35 & 5230.00 & 122.35 & 68.28 & 683.06 & 21.94 & 1.79 \\  & North & 3826 & 0.80 & 0.95 & 1.33 & 1.71 & 113.40 & 4.01 & 1.93 & 287.51 & 14.57 & 2.08 \\  & South & 6924 & 0.17 & 1.23 & 1.49 & 1.75 & 207.80 & 4.62 & 1.92 & 1042.99 & 28.39 & 2.41 \\  & North & 3826 & 1.70 & 1.98 & 2.31 & 3.02 & 100.00 & 5.65 & 3.48 & 151.01 & 10.60 & 1.62 \\  & South & 6924 & 0.03 & 2.32 & 2.87 & 4.25 & 200.00 & 11.33 & 4.61 & 177.67 & 12.27 & 2.46 \\  & North & 3826 & 0.62 & 0.82 & 0.93 & 0.98 & 10.60 & 0.46 & 1.02 & 99.20 & 7.58 & 0.45 \\  & South & 6924 & 0.07 & 0.66 & 0.79 & 1.00 & 382.70 & 4.82 & 1.03 & 5676.49 & 72.44 & 4.68 \\  & North & 3826 & 1.00 & 5.20 & 7.20 & 9.50 & 1912.60 & 52.47 & 12.02 & 662.99 & 23.44 & 4.37 \\  & South & 6924 & 0.84 & 5.95 & 8.89 & 10.88 & 517.94 & 27.71 & 12.87 & 151.28 & 10.95 & 2.15 \\  & North & 3826 & 0.08 & 0.10 & 0.13 & 0.18 & 25.74 & 0.50 & 0.19 & 1796.20 & 38.05 & 2.63 \\  & South & 6924 & 0.02 & 0.17 & 0.25 & 0.30 & 584.60 & 8.06 & 0.59 & 4031.47 & 58.09 & 13.66 \\  & North & 3826 & 8.30 & 14.70 & 19.30 & 24.60 & 473.30 & 15.64 & 21.99 & 206.42 & 9.98 & 0.71 \\  & South & 6924 & 0.52 & 6.59 & 20.00 & 26.10 & 2623.00 & 38.56 & 19.98 & 3055.63 & 48.04 & 1.93 \\  & North & 3826 & 4.00 & 6.90 & 9.00 & 11.50 & 80.10 & 4.94 & 10.02 & 27.94 & 3.80 & 0.49 \\  & South & 6924 & 0.44 & 3.36 & 8.65 & 11.13 & 101.10 & 6.29 & 8.56 & 21.47 & 2.90 & 0.73 \\  & North & 3826 & 0.10 & 0.37 & 0.49 & 0.65 & 946.60 & 19.87 & 1.70 & 1480.40 & 35.13 & 11.69 \\  & South & 6924 & 0.13 & 0.73 & 1.03 & 1.24 & 150.50 & 3.71 & 1.60 & 486.70 & 17.07 & 2.32 \\ \hline \hline \end{tabular} Note: All elements are in units of \(10^{-6}\).  
\end{table} 
Table 3: Statistical characteristics of the raw data. From the coefficient of variation, it is interesting to note that the performance of the same element in the northern and southern regions varies greatly. In terms of the maximum/minimum values, except for As and Sb, all other elements show that the maximum values in the southern region are larger and the minimum values are smaller. From the coefficient of variation, the coefficients for Pb and W are quite similar. For As and Sb, the coefficient of variation in the northern region is significantly higher than that in the southern region. Moreover, nearly all the remaining elements exhibit a much smaller coefficient of variation in the northern region than in the southern region. Generally, a higher coefficient of variation indicates greater variability in the data, which is more favorable for mineralization. However, statistical analysis reveals that the coefficients of variation for the same element in the northern and southern regions differ greatly, with some even being orders of magnitude apart. This is clearly unreasonable for geological interpretation. Therefore, further data processing is required for both datasets.