Data Treatment in Environmental Sciences
eBook - ePub

Data Treatment in Environmental Sciences

  1. 194 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data Treatment in Environmental Sciences

About this book

Data Treatment in Environmental Sciences presents the various methods used in the analysis of databases—obtained in the field or in a laboratory—by focusing on the most commonly used multivariate analyses in different disciplines of environmental sciences, from geochemistry to ecology. The book examines the principles, application conditions and implementation (in R software) of various analyses before interpreting them. The wide variety of analyses presented allows users to treat datasets, both large and small, which are often limited in terms of available processing techniques.The approach taken by the author details (i) the preparation of a dataset prior to analysis, in relation to the scientific strategy and objectives of the study, (ii) the preliminary treatment of datasets, (iii) the establishment of a structure of objects (stations/dates) or relevant variables (e.g. physicochemical, biological), and (iv) how to highlight the explanatory parameters of these structures (e.g. how the physico-chemistry influences the biological structure obtained).- Proposes tools that can be used to deal with environmental data- Insists on the adequacy between the scientific objectives and the types of analyses- Present mathematical principles without going into detail- Offers a wide range of important analyses

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Yes, you can access Data Treatment in Environmental Sciences by Valérie David in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Environmental Science. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title page
  3. Table of Contents
  4. Dedication
  5. Copyright
  6. Introduction
  7. 1: Observing and Preparing a Data Set
  8. 2: Preliminary Treatment of the Data Set
  9. 3: Structure as Groups of Objects/Variables
  10. 4: Structure as Gradients of Objects/Variables
  11. 5: Understanding a Structure
  12. Conclusion
  13. Bibliography
  14. Index