Environmental Life Cycle Assessment Of Goods And Services: An Input-Output Appro Hendrickson, Chris / Lave, Lester / Mattthews, Scott Rff Press Resources For The Future |
Remote Sensing And Gis For Ecologists: Using Open Source Software Wegmann, Martin / Leutner, Benjamin / Dech, Stefan Pelagic Publishing |
Global Change In Multispecies Systems: Part II Woodward, Guy / Jacob, Ute / O'gorman, Eoin Academic Press |
Principles Of Terrestrial Ecosystem Ecology Chapin, Stuart III / Matson, Pamela / Vitousek, Peter Springer Publishing Company |
Freshwater Ecology: Concepts & Environmental Applications Of Limnology Dodds, Walter / Whiles, Matt Academic Press |
Ecosystem Services: From Biodiversity To Society (Part 2) Woodward, Guy / Bohan, David Academic Press |
Título: Ecological Statistics: Contemporary Theory And Application | ||
Autor: Fox, Gordon / Negrete-Yankelevich, Simoneta / Sosa, Vinicio | Precio: $1429.00 | |
Editorial: Oxford University Press | Año: 2015 | |
Tema: Ecologia | Edición: 1ª | |
Sinopsis | ISBN: 9780199672554 | |
The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics.
This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis |