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Design of comparative experiments /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Design of comparative experiments // R.A. Bailey.
Author:	Bailey, R.
Description:	1 online resource (xiii, 330 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Experimental design. -
Online resource:	https://doi.org/10.1017/CBO9780511611483
ISBN:	9780511611483 (ebook)

Design of comparative experiments /
Bailey, R.

Design of comparative experiments /R.A. Bailey. - 1 online resource (xiii, 330 pages) :digital, PDF file(s). - Cambridge series on statistical and probabilistic mathematics ;25. - Cambridge series on statistical and probabilistic mathematics ;32..

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.

ISBN: 9780511611483 (ebook)Subjects--Topical Terms:

527680
Experimental design.

LC Class. No.: QA279 / .B35 2008

Dewey Class. No.: 519.57

Design of comparative experiments /
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520 $a This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.
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