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Statistical Methods for Detection and Quantificati of Environmental Contamination H 400 p. 01

Gibbons, RD  著

在庫状況 海外在庫有り  お届け予定日 20日間  数量 冊 
価格 \45,830(税込)         

発行年月 2001年07月
出版社/提供元
出版国 アメリカ合衆国
言語 英語
媒体 冊子
装丁 hardcover
ページ数/巻数 400 p.
ジャンル 洋書/理工学/環境科学/環境動態解析
ISBN 9780471255321
商品コード 0200101595
本の性格 学術書
商品URL
参照
https://kw.maruzen.co.jp/ims/itemDetail.html?itmCd=0200101595

内容

Comprehensive coverage, state–of–the–art methods This groundbreaking volume describes the statistical theory that underlies the detection and quantification of environmental pollution both in the laboratory and in the field. It presents the foundation of relating measured concentrations to true concentrations and the development of intervals of uncertainty for true concentrations, and it presents a comprehensive review of the problem of estimating thresholds at which detection and quantification decisions can be made reliably. The authors demonstrate the use of analytical measurements in making environmental impact decisions and in comparing environmental data to regulatory standards and naturally occurring background concentrations. Taking the next step in a major evolution in the way environmental impact decisions are made, Statistical Methods for Detection and Quantification of Environmental Contamination: Presents statistical methods that allow the earliest possible detection and quantification of contaminants Describes procedures applicable to all environmental constituents Covers numerous state–of–the–art approaches Includes case studies demonstrating practical applications of these approaches An indispensable handbook for scientists and engineers involved in environmental monitoring programs, this book is also an important resource for public health officials, waste facility managers, regulators, statisticians, and analytical chemists. Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Detection and Quantification of Environmental Contamination was among those chosen.

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