An application of exploratory data analysis (EDA) as a robust non-parametric technique for geochemical mapping in a semi-arid climate

Exploratory data analysis (EDA) techniques based on the boxplot and robust-class selection were applied to the analysis of single-element stream sediment data in the Collo area (N-E Algeria). The area is characterised by many factors that affect data variability: variation of lithology, combined existence of permanent and ephemeral streams, flash floods, rugged terrain, and climate. The boxplot proved to be very useful in capturing the empirical data distribution, the skewness, and in defining outliers. No data transformation was needed prior to the analysis of single element distributions (Cr, Pb, Zn, Cu, As, and Fe) as is the case in classical statistics. Geochemical mapping of these elements was based on resistant class selection as defined by the boxplot. Results showed the close spatial correlation of outlier data for Cr with a plagioclase-lherzolite intrusion and known chromite pods. The geochemical maps of Pb, Zn, Cu and As concentrations showed an association of these elements coincident with known base-metal sulphides and arsenopyrite mineralisation, delineating a northeastern anomaly spreading well over known mineralisation. The choice of the robust classes based on the boxplot also showed the close spatial distribution of Fe with known hematite and magnetite mineralization. EDA techniques proved to be very useful in delineating known mineralisation in the Collo area where stream sediment data is subject to variability owing to many factors (geologic, physiographic and climatic). EDA proved to be a simple and very useful tool in analysing single-element geochemical data. EDA could be used in similar terrains as an alternative to the classical methods where a normality precondition is needed prior to analysis and where class selection may be affected by the presence of “wild” data.