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dc.contributor.authorNguyen, Thi Hai Ly-
dc.contributor.authorLu, Ngoc Tram Anh-
dc.contributor.authorNguyen, Ho-
dc.date.accessioned2022-03-11T03:42:36Z-
dc.date.available2022-03-11T03:42:36Z-
dc.date.issued2021-
dc.identifier.issn0866-7675-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/75095-
dc.description.abstractMultivariate statistics has proven many outstanding advantages and has been used extensively in various studies in the ecological environment field. They supported ecologists to discover the structure and previous relatively objective summary of the primary features of the data. In this paper, some important statistical techniques, including principal component analysis (PCA), canonical correspondence analysis (CCA) and cluster analysis, are explained briefly. Each of them is also examined by a corresponding case-study. The PCA is applied to identify and analyze the relationship between mangrove plant communities and soil factors. Meanwhile, the CCA is put in an application to analyze the relationship between the two sets of species and soil data, from which to determine the effect of soil on the distribution of dominant species. Finally, cluster analysis is examined to analyze the similarities among species in the studied area.vi_VN
dc.language.isoenvi_VN
dc.relation.ispartofseriesDong Thap University Journal of Science;Vol.10, No.05 .- P.115-120-
dc.subjectCanonical correlation analysisvi_VN
dc.subjectCluster analysisvi_VN
dc.subjectData analysisvi_VN
dc.subjectEcologyvi_VN
dc.subjectEnvironmentvi_VN
dc.subjectPrincipal component analysisvi_VN
dc.titleApplication of multivariate statistical analysis in ecological environment researchvi_VN
dc.typeArticlevi_VN
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