Abstract
Data collection of environmental radioactive chemical contaminants is information of fundamental importance for decision-making in environmental planning and management. In this case, data analyses should be performed with a high level of significance within robust statistical planning. The objective of this study was to utilize the Violinplot as a graphical modeling tool for statistical analysis of radioecology data. To achieve this, a computational algorithm was developed in the Python language. The findings clearly demonstrate that the Violinplot is an outstanding data analysis tool for robust statistical planning in environmental management.
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