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Regression Models for the Comparison of Measurement Methods (Paperback, 1st ed. 2020) Loot Price: R1,346
Discovery Miles 13 460
Regression Models for the Comparison of Measurement Methods (Paperback, 1st ed. 2020): Heleno Bolfarine, Mario De Castro,...

Regression Models for the Comparison of Measurement Methods (Paperback, 1st ed. 2020)

Heleno Bolfarine, Mario De Castro, Manuel Galea

Series: SpringerBriefs in Statistics - ABE

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Loot Price R1,346 Discovery Miles 13 460 | Repayment Terms: R126 pm x 12*

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This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others - a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine. Methods comparison involves a non-standard regression problem; when a method is to be tested in a laboratory, it may be used on samples of suitable reference material, but frequently it is used with other methods on a range of suitable materials whose concentration levels are not known precisely. By presenting a sound statistical background not found in other books for the type of problem addressed, this book complements and extends topics discussed in the current literature. It highlights the applications of the presented techniques with the support of computer routines implemented using the R language, with examples worked out step-by-step. This book is a valuable resource for applied statisticians, practitioners, laboratory scientists, geostatisticians, process engineers, geologists and graduate students.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: SpringerBriefs in Statistics - ABE
Release date: October 2020
First published: 2020
Authors: Heleno Bolfarine • Mario De Castro • Manuel Galea
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 64
Edition: 1st ed. 2020
ISBN-13: 978-3-03-057934-0
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
LSN: 3-03-057934-4
Barcode: 9783030579340

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