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Image of - Data Analysis in Vegetation Ecology | Paperback
Data Analysis in Vegetation Ecology | Paperback

Data Analysis in Vegetation Ecology | Paperback

by Wildi

Evolving from years of teaching experience by one of the top experts in vegetation ecology, Data Analysis in Vegetation Ecology aims to explain the background and basics of mathematical (mainly multivariate) analysis of vegetation data. The book lays out the basic operations involved in the analysis, the underlying hypotheses, aims and points of views. It conveys the message that each step in the calculations has a specific, straightforward meaning and that patterns and processes known by ecologists often find their counterpart in mathematical operations and functions. The first chapters introduce the elementary concepts and operations and relate them to real-world phenomena and problems. Later chapters concentrate on combinations of methods to reveal surprising features in data sets. Showing how to find patterns in time series, how to generate simple dynamic models, how to reveal spatial patterns and related occurrence probability maps.

Highlights

  • binding-icon

    9780470661024

    ISBN:

  • binding-icon

    Wildi

    Author:

  • binding-icon

    234

    Pages:

  • binding-icon

    1050 gm

    Weight:

  • langauage-icon

    English

    Language:

  • date-icon

    2010

    Year:

  • edition-icon

    N/A

    Edition:

  • binding-icon

    Paperback

    Binding:

₹5136

₹6420

Evolving from years of teaching experience by one of the top experts in vegetation ecology, Data Analysis in Vegetation Ecology aims to explain the background and basics of mathematical (mainly multivariate) analysis of vegetation data. The book lays out the basic operations involved in the analysis, the underlying hypotheses, aims and points of views. It conveys the message that each step in the calculations has a specific, straightforward meaning and that patterns and processes known by ecologists often find their counterpart in mathematical operations and functions. The first chapters introduce the elementary concepts and operations and relate them to real-world phenomena and problems. Later chapters concentrate on combinations of methods to reveal surprising features in data sets. Showing how to find patterns in time series, how to generate simple dynamic models, how to reveal spatial patterns and related occurrence probability maps.

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