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Cause and correlation in biology : = a user's guide to path analysis, structural equations, and causal inference /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Cause and correlation in biology :/ Bill Shipley.
其他題名:	a user's guide to path analysis, structural equations, and causal inference /
其他題名:	Cause & Correlation in Biology
作者:	Shipley, Bill,
面頁冊數:	1 online resource (xii, 317 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Biometry. -
電子資源:	https://doi.org/10.1017/CBO9780511605949
ISBN:	9780511605949 (ebook)

Cause and correlation in biology : = a user's guide to path analysis, structural equations, and causal inference /
Shipley, Bill,1960-

Cause and correlation in biology :a user's guide to path analysis, structural equations, and causal inference /Cause & Correlation in BiologyBill Shipley. - 1 online resource (xii, 317 pages) :digital, PDF file(s).

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

This book goes beyond the truism that 'correlation does not imply causation' and explores the logical and methodological relationships between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct randomised or experimentally controlled experiments. Many of these methods are quite new and most are generally unknown to biologists. In addition to describing how to conduct these statistical tests, the book also puts the methods into historical context and explains when they can and cannot justifiably be used to test or discover causal claims. Written in a conversational style that minimises technical jargon, the book is aimed at practising biologists and advanced students, and assumes only a very basic knowledge of introductory statistics.

ISBN: 9780511605949 (ebook)Subjects--Topical Terms:

598268
Biometry.

LC Class. No.: QH323.5 / .S477 2000

Dewey Class. No.: 570/.1/5195

Cause and correlation in biology : = a user's guide to path analysis, structural equations, and causal inference /
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520 $a This book goes beyond the truism that 'correlation does not imply causation' and explores the logical and methodological relationships between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct randomised or experimentally controlled experiments. Many of these methods are quite new and most are generally unknown to biologists. In addition to describing how to conduct these statistical tests, the book also puts the methods into historical context and explains when they can and cannot justifiably be used to test or discover causal claims. Written in a conversational style that minimises technical jargon, the book is aimed at practising biologists and advanced students, and assumes only a very basic knowledge of introductory statistics.
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