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Visualisation and permutation methods for archaeological data analysis

Visualisation and permutation methods for archaeological data analysis Archaeologists routinely analyse bivariate data, whether in raw form or as output from principal components or discriminant function analyses. Often, the aim is to test hypotheses regarding the relationships between two or more groups of data. This paper demonstrates two techniques that are rarely used in archaeology yet, together, refine the presentation and testing of such relationships. Confidence ellipses provide statistically meaningful summaries of location and dispersion, and allow the analyst to judge the feasibility of hypotheses. Permutation tests provide analogues of parametric statistics but do not require the sampling or distributional assumptions that such tests demand; further to this, they have greater statistical power than non-parametric statistics. The value of these two methods in combination is illustrated via a case study of stable isotope ratio data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archaeological and Anthropological Sciences Springer Journals

Visualisation and permutation methods for archaeological data analysis

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References (45)

Publisher
Springer Journals
Copyright
Copyright © 2013 by Springer-Verlag Berlin Heidelberg
Subject
Earth Sciences; Earth Sciences, general; Archaeology; Chemistry/Food Science, general; Geography (general); Life Sciences, general; Anthropology
ISSN
1866-9557
eISSN
1866-9565
DOI
10.1007/s12520-013-0158-z
Publisher site
See Article on Publisher Site

Abstract

Archaeologists routinely analyse bivariate data, whether in raw form or as output from principal components or discriminant function analyses. Often, the aim is to test hypotheses regarding the relationships between two or more groups of data. This paper demonstrates two techniques that are rarely used in archaeology yet, together, refine the presentation and testing of such relationships. Confidence ellipses provide statistically meaningful summaries of location and dispersion, and allow the analyst to judge the feasibility of hypotheses. Permutation tests provide analogues of parametric statistics but do not require the sampling or distributional assumptions that such tests demand; further to this, they have greater statistical power than non-parametric statistics. The value of these two methods in combination is illustrated via a case study of stable isotope ratio data.

Journal

Archaeological and Anthropological SciencesSpringer Journals

Published: Sep 20, 2013

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