Statistical methods in ecological data analysis

Jayasankar, J (2017) Statistical methods in ecological data analysis. In: Winter School on Structure and Function of the Marine Ecosystem : Fisheries, 1-21 December 2017, Kochi.

[img]
Preview
Text
Winter School on Structure and Functions of Ecosystem_12.pdf

Download (226kB) | Preview
Related URLs:

    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 non-frequentist 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: Conference or Workshop Item (Paper)
    Subjects: Marine Fisheries > Fisheries Statistics
    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: 28 May 2018 09:02
    Last Modified: 28 May 2018 09:02
    URI: http://eprints.cmfri.org.in/id/eprint/12758

    Actions (login required)

    View Item View Item