Multivariate Statistics for Wildlife and Ecology Research
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Description: 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 more applicable to their course of study. Multivariate Statistics for Wildlife and Ecology Research gives the reader a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and underlying theory. More important, the reader will gain insight into the type of research questions best handled by each technique and the important considerations in applying each one. Whether used as a textbook for specialized courses or as a supplement to general statistics texts, the book emphasizes those techniques that students of ecology and natural resources most need to understand and employ in their research. Detailed examples use real wildlife data sets analyzed using the SAS statistical software program.The book is specifically targeted for upper-division and graduate students in wildlife biology, forestry, and ecology, and for professional wildlife scientists and natural resource managers, but it will be valuable to researchers in any of the biological sciences.Kevin McGarigal is Assistant Professor and Sam Cushman is a doctoral candidate in the Department of Forestry and Wildlife Management at the University of Massachusetts. Susan Stafford is Head of the Forest Science Department at Colorado State University.
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All the information you need in one place! Each Study Brief is a summary of one specific subject; facts, figures, and explanations to help you learn faster.
Copyright year: 2000
Publication date: 3/1/2002
Size: 5.75" wide x 9.00" long x 0.50" tall
|Introduction & Overview|
|Ordination: Principal Components Analysis Chapter|
|Discriminant Analysis Chapter|
|Canonical Correlation Analysis|
|Summary And Comparison|