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Multivariate Statistics for Wildlife and Ecology Research

Wildlife researchers and ecologists make widespread use of multivariate statistics in their studies. With its focus on the practical application of the techniques of multivariate statistics, this book shapes the powerful tools of statistics for the specific needs of ecologists and makes statistics m...

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Bibliographic Details
Main Authors: McGarigal, Kevin, Cushman, Samuel A. (Author), Stafford, Susan (Author)
Format: eBook
Language:English
Published: New York, NY Springer New York 2000, 2000
Edition:1st ed. 2000
Subjects:
Mathematical Applications In Environmental Science
Mathematical And Computational Biology
Biostatistics
Biomathematics
Animal Culture
Theoretical And Statistical Ecology
Animal Science
Ecology 
Environmental Sciences / Mathematics
Ecology
Biometry
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 3.8 Evaluating the Stability of the Cluster Solution
  • 3.9 Complementary Use of Ordination and Cluster Analysis
  • 3.10 Limitations of Cluster Analysis
  • Appendix 3.1
  • 4 Discriminant Analysis
  • 4.1 Objectives
  • 4.2 Conceptual Overview
  • 4.3 Geometric Overview
  • 4.4 The Data Set
  • 4.5 Assumptions
  • 4.6 Sample Size Requirements
  • 4.7 Deriving the Canonical Functions
  • 4.8 Assessing the Importance of the Canonical Functions
  • 4.9 Interpreting the Canonical Functions
  • 4.10 Validating the Canonical Functions
  • 4.11 Limitations of Discriminant Analysis
  • Appendix 4.1
  • 5 Canonical Correlation Analysis
  • 5.1 Objectives
  • 5.2 Conceptual Overview
  • 5.3 Geometric Overview
  • 5.4 The Data Set
  • 5.5 Assumptions
  • 5.6 Sample Size Requirements
  • 5.7 Deriving the Canonical Variates
  • 5.8 Assessing the Importance of the Canonical Variates
  • 5.9 Interpreting the Canonical Variates
  • 5.10 Validating the Canonical Variates
  • 5.11 Limitations of Canonical Correlation Analysis
  • Appendix 5.1
  • 6 Summary and Comparison
  • 6.1 Objectives
  • 6.2 Relationship Among Techniques
  • 6.3 Complementary Use of Techniques
  • Appendix: Acronyms Used in This Book.
  • 1 Introduction and Overview
  • 1.1 Objectives
  • 1.2 Multivariate Statistics: An Ecological Perspective
  • 1.3 Multivariate Description and Inference
  • 1.4 Multivariate Confusion!
  • 1.5 Types of Multivariate Techniques
  • 2 Ordination: Principal Components Analysis
  • 2.1 Objectives
  • 2.2 Conceptual Overview
  • 2.3 Geometric Overview
  • 2.4 The Data Set
  • 2.5 Assumptions
  • 2.6 Sample Size Requirements
  • 2.7 Deriving the Principal Components
  • 2.8 Assessing the Importance of the Principal Components
  • 2.9 Interpreting the Principal Components
  • 2.10 Rotating the Principal Components
  • 2.11 Limitations of Principal Components Analysis
  • 2.12 R-Factor Versus Q-Factor Ordination
  • 2.13 Other Ordination Techniques
  • Appendix 2.1
  • 3 Cluster Analysis
  • 3.1 Objectives
  • 3.2 Conceptual Overview
  • 3.3 The Definition of Cluster
  • 3.4 The Data Set
  • 3.5 Clustering Techniques
  • 3.6 Nonhierarchical Clustering
  • 3.7 Hierarchical Clustering

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