Environment and Ecology Research Vol. 4(1), pp. 21 - 29
DOI: 10.13189/eer.2016.040104
Reprint (PDF) (260Kb)


Multivariate Statistical Methods in Researching Biocultural Diversity


Joško Sindik , Jelena Šarac *
Institute for Anthropological Research, Croatia

ABSTRACT

Nonlinear multivariate statistical methods have proven to be useful tools in research issues dealing with biocultural diversity. Namely, these methods have less restrictions in their use, as compared with compatible linear methods. This research is the example of using some of these methods. The three indices of biocultural diversity by the variables of biological and cultural diversity have been predicted, based on population size (POP), areal size (AREA) and overall biological and cultural richness (RICH). Then, we have determined: clusters in which different countries can be grouped based on biocultural diversity indices (POP, AREA, RICH), the latent dimensions of the biocultural diversity in the space of biocultural diversity indices (POP, AREA, RICH) and finally, the association between the indices of biodiversity and cultural diversity (POP, AREA, RICH). General conclusion is that nonlinear multivariate methods (together with cluster analysis), in spite of their robustness, can provide useful information to the researchers, on the issues they are interested in (in this example, about biocultural diversity). Of course, these methods are more convenient than linear methods only in the context of absence of clear linear relationships between the variables of interest, while the overfitting problem couldn't be avoided in both cases.

KEYWORDS
Association, Biodiversity, Biocultural and Cultural Diversity, Nonlinear Methods

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Joško Sindik , Jelena Šarac , "Multivariate Statistical Methods in Researching Biocultural Diversity," Environment and Ecology Research, Vol. 4, No. 1, pp. 21 - 29, 2016. DOI: 10.13189/eer.2016.040104.

(b). APA Format:
Joško Sindik , Jelena Šarac (2016). Multivariate Statistical Methods in Researching Biocultural Diversity. Environment and Ecology Research, 4(1), 21 - 29. DOI: 10.13189/eer.2016.040104.