Catalogue


The interpretation of ecological data : a primer on classification and ordination /
E.C. Pielou.
imprint
New York : Wiley, c1984.
description
xi, 263 p. : ill. ; 24 cm.
ISBN
0471889504 :
format(s)
Book
Holdings
More Details
imprint
New York : Wiley, c1984.
isbn
0471889504 :
general note
"A Wiley-Interscience publication."
catalogue key
2933433
 
Includes bibliographical references (p. 257-259) and index.
A Look Inside
Full Text Reviews
Appeared in Choice on 1985-09:
The ``ecological data'' referred to by the title are species population counts within defined survey areas. This is a textbook for population biologists on how to apply sound mathematical statistics (including rather sophisticated matrix algebra) to raw population data. Pielou has taken care to spell out intermediate steps in mathematical derivations, and to define all terms. Learning aids include a glossary and bibliography, a few problems at chapter ends, and solutions to these in an appendix. The writing style is unusually clear and direct, even for a textbook, and is at a level that respects the reader's presumed intelligence and ignorance. The only cavils this reviewer finds are a rather skimpy index (some 200 entries, many of them the names of authors cited), and a too broad title that might, for example, have referred to remote sensing or chemical sampling of ecosystems. Highly recommended for undergraduate libraries supporting courses in quantitative biology, paleontology, and mathematical ecology.-T.R. Blackburn, St. Andrews Presbyterian College
Reviews
This item was reviewed in:
Choice, September 1985
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Summaries
Main Description
A detailed introduction to the methods used by ecologists--classification and ordination--to clarify and interpret large, unwieldy masses of multivariate field data. Permits ecologists to understand, not just mechanically use, pre-packaged programs for multivariate analysis. Demonstrates these techniques using artificial data simple enough for every analytical step to be understood.
Table of Contents
Classification by Clustering
Transforming Data Matrices
Ordination
Divisive Classification
Discriminant Ordination
Answers to Exercises
Glossary
Bibliography
Index
Table of Contents provided by Publisher. All Rights Reserved.

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