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Multivariate Statistics for Wildlife and Ecology Research
 
 
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Multivariate Statistics for Wildlife and Ecology Research [Hardcover]

Kevin McGarigal (Author), Sam Cushman (Author), Susan Stafford (Author)
4.5 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

0387988912 978-0387988917 June 16, 2000 1
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. It gives readers a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and the underlying theory. More importantly, the reader will gain insight into the type of research questions best handled by each technique and the important considerations in applying them. Whether used as a textbook for specialised courses or as a supplement to general statistics texts, the book emphasises those techniques that students of ecology and natural resources most need to understand and employ in their research. While targeted for upper-division and graduate students in wildlife biology, forestry, and ecology, and for professional wildlife scientists and natural resource managers, this book will also be valuable to researchers in any of the biological sciences.

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Product Details

  • Hardcover: 296 pages
  • Publisher: Springer; 1 edition (June 16, 2000)
  • Language: English
  • ISBN-10: 0387988912
  • ISBN-13: 978-0387988917
  • Product Dimensions: 9.3 x 6.3 x 1.2 inches
  • Shipping Weight: 1.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #3,922,733 in Books (See Top 100 in Books)

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Average Customer Review
4.5 out of 5 stars (4 customer reviews)
 
 
 
 
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1 of 1 people found the following review helpful:
4.0 out of 5 stars Applied, don't need a PhD to understand; lacks theory, October 4, 2009
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This book is very applied and the practitioner with little statistical knowledge will be able to benefit from it. It is easy to read and has many examples. I would say that it is written for MS level grad students. I find it very useful for examples of application.
There is not much theory and if you are looking to see how the techniques are founded in first principles, this is not the book for you. If you just want to know how to do it and not concerned too much with underlying theory, you will enjoy this.
This is a good overview of the techniques and what they can do. If you end up using a technique, you might want to find a different text to explore the theory more if that is your desire.
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1 of 1 people found the following review helpful:
5.0 out of 5 stars Invaluable for a grad student!, September 25, 2008
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chickadee "birdnerd" (behind the zion curtain, ut) - See all my reviews
This book is easy to read and includes many real world examples. I appreciate that it is not too heavy on the statistical semantics which I can get from other books. I like the fact that people on many levels can read this book and understand the statistical methods without being overly intimidated by them. I return to this book time and time again during the course of my graduate studies.
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3 of 4 people found the following review helpful:
4.0 out of 5 stars A good introduction to multivariate statistics, January 25, 2007
This book is fairly easy to understand, even with little knowledge of multivariate statistics. The author uses specific examples relevant to ecological fields and does not focus on theory (which is a rarity in statistical manuals). It is, however, starting to get a bit outdated with some of the techniques gaining favor in the literature recently.
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Inside This Book (learn more)
First Sentence:
By the end of this chapter, you should be able to do the following: Recognize the types of research questions that are best handled with a multivariate analysis. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
raw covariance matrix, sampling entities, agglomeration sequence, complemented coefficient, ith canonical function, relative percent variance, unconstrained ordination methods, floristic variables, ith canonical variate, placing similar entities, standardized canonical scores, sampling entity, categorical grouping variable, eigenanalysis problem, meaningful ecological interpretation, percent variance criterion, equal frequency ellipses, latent root criterion, assess skewness, high canonical correlation, geometric overview, new composite dimensions, output dissimilarities, standardized canonical coefficients, raw canonical coefficients
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Forest Service General Technical Report, Academic Press, Conceptual Overview, Journal of Wildlife Management, Sites Sites, Std Mean, Conservation Biology, Lowest Obs Highest Obs, Moments Stem Leaf, Multivariate Data Analysis, Normal Probability Plot, Oregon Coast Range, Sgn Rank, American Statistician, Biological Conservation, Ecological Monographs, Multivariate Statistical Methods, Std Dev, Sum Wgts, Avian Biol, Cambridge University Press, Journal of Marketing Research, Multivariate Confusion, Multivariate Statistical Analysis
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