Which all statistical tests should be carried out for interpreting geochemical data set to find differences among sites, seasons, metal species, ionic bonding, etc.
This question is equivalent to asking what treatment should be given to a person suffering from a disease?
Well, the choice of the statistical evaluation depends strongly on the character of the data and on the objectives of the study. This question is too general, sorry
There are two end-member approaches to finding patterns in geochemical data—unsupervised learning and supervised learning. Although the unsupervised learning approach has been recommended widely and has been successful in many situations, some tools ex- ist that offer the possibility of reducing the risk of exploration and resource assessments.
Most regional geochemistry data should be trans- formed and standardized via a Z score. Relations among geochemical variables can be used in some situations to estimate values that are reported to be below detection limits—this could be helpful in deter- mining the linkage of geologic units to geochemistry. Supervised learning methods, such as discrimi- nant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased es- timates of where mineralization might exist.
Your geochemical data if well analyzed can be used in your discriminant statistical interpretation of geologic processes. A geochemist can be sought for your sample analysis.
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