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The statistics of counting clasts in rudites: a review, with examples from the upper Palaeogene of southern California, USA
Author(s) -
HOWARD JEFFREY L.
Publication year - 1993
Publication title -
sedimentology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.494
H-Index - 108
eISSN - 1365-3091
pISSN - 0037-0746
DOI - 10.1111/j.1365-3091.1993.tb01759.x
Subject(s) - paleogene , geology , clastic rock , paleontology , sedimentary rock , cretaceous
The relative proportions of gravel sized particles of different lithology in rudaceous sedimentary rocks are generally determined in the field by clast counting. Clast counts are usually carried out qualitatively in order to assess sedimentary provenance. However, a review of the statistical aspects of clast counting suggests that this technique also can be applied quantitatively, and to investigate a variety of other objectives during basin analysis. Geographical and stratigraphical changes in the relative proportions of clasts can be quantified statistically and used to characterize sediment dispersal patterns in space and time, respectively. Statistical comparisons between clast assemblages can be used as a tool to match up rock units. This approach may help to constrain tectonic or suspect‐terrane models, or to document sediment recycling. Both counting and sampling errors contribute to the total probable error of a clast count. Sampling error results from the uneven distribution of clasts in outcrop, perhaps caused by selective sorting. Counting error arises from a count of some number less than the total number of clasts in the population. Sampling and counting errors can be minimized by counting in closely spaced subsets, and by counting a total of at least 400 clasts, respectively. Thus, a useful procedure is to count four closely spaced subsets of 100 each, and combine the results for a total of 400. Point counting should not be used because differences in particle size produce biased results. A better method is to count all clasts above some minimum size within a specified area of outcrop. Analysis of upper Palaeogene non‐marine conglomerates composing part of the Sespe Formation in California, using confidence intervals, hypothesis testing, analysis of variance, ratio analysis and varietal studies, demonstrates that useful statistics can be derived by counting clasts.

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