Statistical Methods in Ecological Data Analysis

Jayasankar, J (2022) Statistical Methods in Ecological Data Analysis. In: ICAR-CMFRI -Winter School on Recent Development in Taxonomic Techniques of Marine Fishes for Conservation and Sustainable Fisheries Management. ICAR-Central Marine Fisheries Research Institute, Kochi, pp. 551-555.

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    Abstract

    Although analytical methods in statistics have all along been generic and evolutionary in the first half of past century, the developments happening in the field of computational statistics in the past couple of decades are more need based and custom tuned. A lot of effort is being put in by researchers in bundling methods, theory and procedures in classical statistical literature on their common applicability to a targeted exploration. It is common place to collate various univariate, multivariate, parametric, non-parametric, frequentist and nonfrequentist methods, which have applications in different domains like ecology, clinical trials, bioinformatics etc. and tag them as per the domain subject matter. Thus the generic and specific procedures which are of relevance in exploratory and confirmatory analyses in the field of ecological studies of communities have been grouped under a common pivot. During the course of this discussion a couple of such statistical methods used in community structure studies would be dwelled upon.

    Item Type: Book Section
    Subjects: Oceanography > Remote sensing
    Marine Fisheries > Fisheries Statistics
    Fish and Fisheries > Fish Taxonomy
    Divisions: CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Subject Area > CMFRI > CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Subject Area > CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Depositing User: Arun Surendran
    Date Deposited: 29 Jan 2022 07:03
    Last Modified: 11 Feb 2022 04:34
    URI: http://eprints.cmfri.org.in/id/eprint/15730

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