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Ecological methodology / Charles J. Krebs

Por: Tipo de material: TextoTextoEditor: Menlo Park, CA : Benjamin Cummings, c1999Edición: 2 edDescripción: xii, 620 p. : il. ; 24 cmISBN:
  • 0321021738
Tema(s): Clasificación CDD:
  • 577.0727 E2 1998
Recursos en línea: Resumen: This coherent text translates the methods of statisticians into ecological English so that students may readily apply these methods to the real world. Ecological Methodology, Second Edition provides a balance of material on animal and plant populations. It teaches students of ecology how to design the most efficient tests in order to obtain maximum precision with minimal work. The first part of the text focuses on biological and technical issues in statistical methodology. Students learn about advances that have been made in designing better sampling devices, along with the techniques and equipment used for sampling. The second part deals with creating solid statistical design, and presents all methods that are well-known to statisticians in a language and context that students will easily understand.
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Item type Current library Collection Call number Status Date due Barcode
Libros impresos Libros impresos UCIA UCIA-Cancún UCIA 577.0727 E2 1998 (Browse shelf(Opens below)) Available 8733

Incluye referencia bibliográfica: p. 581-605 e índice

This coherent text translates the methods of statisticians into ecological English so that students may readily apply these methods to the real world. Ecological Methodology, Second Edition provides a balance of material on animal and plant populations. It teaches students of ecology how to design the most efficient tests in order to obtain maximum precision with minimal work. The first part of the text focuses on biological and technical issues in statistical methodology. Students learn about advances that have been made in designing better sampling devices, along with the techniques and equipment used for sampling. The second part deals with creating solid statistical design, and presents all methods that are well-known to statisticians in a language and context that students will easily understand.

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