A Computational Approach to Statistical Arguments in Ecology and Evolution

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Title: A Computational Approach to Statistical Arguments in Ecology and Evolution
Description: Scientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their own research.
Authors: George F. Estabrook
Resource Type: eBook.
Subjects: Biometry--Data processing, Ecology--Statistical methods--Data processing, Evolution (Biology)--Statistical methods--Data processing
Categories: NATURE / Reference, SCIENCE / Life Sciences / Biology, SCIENCE / Life Sciences / General
Database: eBook Collection (EBSCOhost)
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 400628
RelevancyScore: 1038
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1037.72192382813
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  Data: A Computational Approach to Statistical Arguments in Ecology and Evolution
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  Label: Description
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  Data: Scientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their own research.
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  Data: <searchLink fieldCode="DE" term="%22Biometry--Data+processing%22">Biometry--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Ecology--Statistical+methods--Data+processing%22">Ecology--Statistical methods--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Evolution+%28Biology%29--Statistical+methods--Data+processing%22">Evolution (Biology)--Statistical methods--Data processing</searchLink>
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RecordInfo BibRecord:
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    Classifications:
      – Code: 570.15195
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Biometry--Data processing
        Type: general
      – SubjectFull: Ecology--Statistical methods--Data processing
        Type: general
      – SubjectFull: Evolution (Biology)--Statistical methods--Data processing
        Type: general
    Titles:
      – TitleFull: A Computational Approach to Statistical Arguments in Ecology and Evolution
        Type: main
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          Name:
            NameFull: George F. Estabrook
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            NameFull: George F. Estabrook
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2011
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9781107004306
            – Type: isbn-electronic
              Value: 9781139128223
          Titles:
            – TitleFull: A Computational Approach to Statistical Arguments in Ecology and Evolution
              Type: main
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