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

Tipo de material: Libro
 impreso(a) 
 
  y electrónico  
  Libro impreso(a) y electrónico Idioma: Inglés Detalles de publicación: Oxford, England Oxford University Press c2015Descripción: xv, 389 páginas centímetrosISBN:
  • 0199672555
  • 9780199672554
Tema(s): Formatos físicos adicionales: Ecological statistics: contemporary theory and applicationClasificación:
  • 577.015195 E2
Recursos en línea: Formatos físicos adicionales disponibles:
  • Disponible en línea
Resumen:
Inglés

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.

Número de sistema: 57780
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Tipo de ítem Biblioteca actual Colección Signatura topográfica Estado Fecha de vencimiento Código de barras
Libros Biblioteca Chetumal 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 Acervo General (AG) Acervo General 577.015195 E2 Prestado 26/05/2025 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. Inglés

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