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Ecological statistics: contemporary theory and application / edited by Gordon A. Fox, Simoneta Negrete-Yankelevich, Vinicio J. Sosa

Fox, Gordon A [editor/a] | Negrete-Yankelevich, Simoneta [editor/a] | Sosa, Vinicio J [editor/a].
Tipo de material: Libro impreso(a) y electrónico Libro impreso(a) y electrónico Editor: Oxford, England: Oxford University Press, c2015Descripción: xv, 389 páginas ; centímetros.ISBN: 0199672555; 9780199672554.Tema(s): Ecología | Métodos estadísticosFormatos físicos adicionales: Ecological statistics: contemporary theory and applicationClasificación: 577.015195 / E2 Nota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso Nota de bibliografía: Incluye bibliografía: páginas 354-378 e índice: páginas 379-389 Número de sistema: 57780
Resumen:
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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. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

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Libros Biblioteca Chetumal

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Acervo General (AG) 		Acervo General 577.015195 E2 Disponible ECO030008736
Libros Biblioteca Electrónica
Recursos en línea (RE) 		Acervo General Recurso digital ECO400577806897
Libros Biblioteca San Cristóbal

Texto en la configuración de la biblioteca San Cristóbal

Acervo General (AG) 		Acervo General 577.015195 E2 Prestado 31/08/2024 ECO010018496

Incluye bibliografía: páginas 354-378 e índice: páginas 379-389

Glossary: páginas 345-353

Disponible para usuarios de ECOSUR con su clave de acceso

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. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language. eng

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