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Areal Variation and Statistical Correlation

  • William C. Krumbein
Part of the Computer Applications in the Earth Sciences book series (CAES)

Abstract

Correlations introduced between pairs of otherwise statistically independent and uncorrelated variates by similarity in their areal map patterns can be evaluated by partitioning the observed variance-covariance matrices into a trend component and a residual. If the original variates are correlated and have areal trends as well, the problem becomes complicated for sedimentological studies in which only one sample can be taken at any given map point. The situation becomes even more complicated when initially open data are closed, as by taking percentages.

This paper reviews the topic in terms of as yet unpublished work in the past two years. Several possible sources of covariance in sedimentary data are discussed, and it is emphasized that although the effect of map trends can be satisfactorily estimated, some other covariance components are confounded with residual effects. The general conclusion is reached that sedimentological correlation studies of environmental areas need to be supplemented by trend analysis to detect situations in which a seeming correlation is simply the result of similar areal responses by a given pair of variates to a common set of environmental conditions.

Keywords

Statistical Correlation Point Correlation Covariance Component Trend Component Areal Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Plenum Press, New York 1972

Authors and Affiliations

  • William C. Krumbein
    • 1
  1. 1.Northwestern UniversityUSA

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