Multivariate Statistical Methods As A Tool In The Interpretation Of Heavy Mineral Data. A Case Study On Statistical Pattern Recognition Of Earth Data

In the study 208 heavy mineral concentrates (pan samples) from Jameson Land, East Greenland, are considered. Each concentrate has been analysed (by spectroscopy) for the content of (approx.) 25 elements. Furthermore the exact sampling position and the geological characteristics of the environment have been registered. In the study is shown how different multivariate methods combined with geological knowledge of the area can be used in the interpretation and classification of the data. Special emphasis is put on the problem of finding reliable expressions for the background level of the element concentrations in the area. This is done by means of severel discrimination procedures. The other main subject is a demonstration of the applicability of isoscore maps - originating from factor analyses - in the evaluation of the co-variability of the data, and thus give another way of classifying the individual samples according to the content of different elements.