Practical Statistics for the Analytical Scientist: A Bench Guide Paperback - 2009
by Bedson, Peter
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Details
- Title Practical Statistics for the Analytical Scientist: A Bench Guide
- Author Bedson, Peter
- Binding Paperback
- Edition 2
- Condition Used: Good
- Pages 282
- Volumes 1
- Language ENG
- Publisher Brand: Royal Society of Chemistry
- Publication date 2009-09-04
- Features Index, Table of Contents
- Bookseller's Inventory # SONG0854041311
- ISBN 9780854041312 / 0854041311
- Weight 1.15 lbs (0.52 kg)
- Dimensions 9.6 x 7.4 x 0.7 in (24.38 x 18.80 x 1.78 cm)
- Size 7.44x0.70x9.69
- Category Science
- Library of Congress subjects Chemometrics
- Dewey Decimal Code 543.015
- Quantity available 1
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From the publisher
From the rear cover
The application of statistics is central to the assessment of data quality and an understanding of statistics is essential for the interpretation of analytical results. 'Practical Statistics for the Analytical Scientist, A Bench Guide' was first published by the RSC in 1997. This well structured manual was designed to help practicing analytical scientists and students identify the correct statistical parameters and tests to apply to their data. Completely revised and updated, the second edition contains new sections on method validation, measurement uncertainty, effective experimental design and proficiency testing. Key features: -covers the essential statistics required in analytical science -describes the application of statistics in important quality assurance activities such as method validation, evaluating uncertainty and proficiency testing -aimed at analysts who may have little knowledge of statistics -focuses on applications rather than theory -'FAQs' in the introduction guide the reader to appropriate chapters -comprehensive list of symbols and notation -extensive worked examples illustrate key statistical techniques -self-assessment questions (with detailed solutions) to test understanding. The book the reader with a set of statistical tools to help them plan effective experiments and apply appropriate statistics for data evaluation.