3 edition of course in mathematical and statistical ecology found in the catalog.
course in mathematical and statistical ecology
Includes bibliographical references (p. -280) and index
|Statement||by Anil Gore and Sharayu Paranjpe|
|Series||Theory and decision library -- v. 42|
|LC Classifications||QH541.15.M34 G67 2001|
|The Physical Object|
|Pagination||xi, 286 p. :|
|Number of Pages||286|
|LC Control Number||00050669|
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E-BOOK EXCERPT. Covering a wide range of disciplines, this book explains the formulae, techniques, and methods used in field ecology. By providing an awareness of the statistical foundation for existing methods, the book will make biologists more aware of the strengths and possible weaknesses of procedures employed, and statisticians more appreciative of the needs of the field ecologist.
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Beginning with classical mathematical models for. We were no exceptions and when opportunity to interact with ecologists as statistreal consultants came, we found ourselves reading more and more of ecology and evolution ary biology. Several years ago we proposed starting of an elective one semester course on statistical ecology for graduate students of statistics of Pune University.
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Ships from and sold by s: 1. for introducing me to mathematical and statistical ecology. My parents, Joan and Ethan Bolker, for thorough and thoughtful com-ments on the manuscript and for establishing the expectation that writing books is just what people do.
And last but not least Aidan and especially Tara for their love, pa-tience and support. Essentially, all models are.
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The book was about halfofthe complete course, the rest being statistical modelling. Concepts in this course will be developed in greater mathematical rigor later in the statistical curriculum, including in STAT,and It is intended to be the first course in statistics taken by math majors interested in statistics.Mathematical Ecology This course considers models, methods, and issues in population ecology.
Topics include the effects of density dependence, delays, demographic stochasticity, and age structure on population growth; population interactions (predation, competition, and mutualism); and applications of optimal control theory to the management.Akira Namatame and Shu-Heng Chen.
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