Sampling Theory: For the Ecological and Natural Resource Sciences
Language: English
Published by OUP Oxford, 2019
- Hardcover
- New

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Add to basketSeller Inventory # V9780198815792
- Title
- Sampling Theory: For the Ecological and Natural Resource Sciences
- Author
- Hankin, David; Mohr,
- Publisher
- OUP Oxford
- Publication year
- 2019
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0198815794
- ISBN 13
- 9780198815792
Sampling Theory is an introductory textbook suitable for advanced undergraduates, graduate students, professional researchers, and practitioners in the fields of ecology, evolution, conservation biology, and natural resource sciences (including fisheries, wildlife, rangeland, ecology and forestry).
"Synopsis" may belong to another edition of this title.
About the Author
Michael S. Mohr is Supervisory Mathematical Statistician and Fisheries Assessment Program Leader for NOAA Fisheries, Southwest Fisheries Science Center, Fisheries Ecology Division, and a Research Fellow at the Institute of Marine Sciences, University of California, Santa Cruz. He holds a Bachelor of Arts degree in Mathematics and a Master of Science degree in Fisheries Science from Humboldt State University and received post-graduate training in Statistics at the University of California, Berkeley. He has over 30 years of experience in quantitative population assessment, applying sampling theory to resource management problems, and developing statistical methods and estimators.
Ken B. Newman is principal researcher in statistical methodology for Biomathematics & Statistics Scotland and reader in the School of Mathematics, University of Edinburgh. He has a PhD in statistics from the University of Washington. From 1993 through 2003 he was on the faculty of the Division of Statistics at the University of Idaho and then moved to the University of St Andrews as a senior lecturer with a joint appointment in the Centre for Ecological and Environmental Modelling. Between 2006 and 2017, he was a mathematical statistician for the US Fish and Wildlife Service where he developed sampling designs for aquatic species and methods for estimating fish abundances and modeling fish population dynamics. His current position includes developing and applying statistical methods for agricultural and environmental processes as well as teaching Bayesian statistics.
"About the title" may belong to another edition of this title.
Kennys Bookstore
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