Quantifying Uncertainty in Analytical Measurement
Author: Eurachem/CITAC Working Group
Publisher:
Published: 2000-01-01
Total Pages: 120
ISBN-13: 9780948926150
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Quantifying Uncertainty in Nuclear Analytical Measurements
Author:
Publisher:
Published: 2004
Total Pages: 268
ISBN-13:
DOWNLOAD EBOOKDedicated specifically to nuclear analytical techniques, this publication is intended to assist scientists using alpha, beta and gamma spectrometries, neutron activation and XRF analyses, and other nuclear analytical methods, in assessing and quantifying the sources of uncertainty in their daily measurements.
Measurement Uncertainty in Chemical Analysis
Author: Paul De Bièvre
Publisher: Springer Science & Business Media
Published: 2013-06-29
Total Pages: 294
ISBN-13: 3662051737
DOWNLOAD EBOOKIt is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.
Quantifying Uncertainty in Subsurface Systems
Author: Céline Scheidt
Publisher: John Wiley & Sons
Published: 2018-06-19
Total Pages: 306
ISBN-13: 1119325838
DOWNLOAD EBOOKUnder the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge. Volume highlights include: A multi-disciplinary treatment of uncertainty quantification Case studies with actual data that will appeal to methodology developers A Bayesian evidential learning framework that reduces computation and modeling time Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians. Read the Editors' Vox: eos.org/editors-vox/quantifying-uncertainty-about-earths-resources
An Introduction to Uncertainty in Measurement
Author: L. Kirkup
Publisher: Cambridge University Press
Published: 2006-06-01
Total Pages: 196
ISBN-13: 1139454900
DOWNLOAD EBOOKMeasurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.
Quantification, Validation and Uncertainty in Analytical Sciences
Author: Max Feinberg
Publisher: John Wiley & Sons
Published: 2024-02-16
Total Pages: 341
ISBN-13: 3527845267
DOWNLOAD EBOOKQuantification, Validation and Uncertainty in Analytical Sciences Companion guide explaining all processes in measuring uncertainty in quantitative analytical results Quantification, Validation and Uncertainty in Analytical Sciences provides basic and expert knowledge by building on the sequence of operations starting from the quantification in analytical sciences by defining the analyte and linking it to the calibration function. Proposing a comprehensive approach to MU (Measurement Uncertainty) estimation, it empowers the reader to apply Method Accuracy Profile (MAP) efficiently as a statistical tool in measuring uncertainty. The text elucidates several examples and template worksheets explaining the theoretical aspects of the procedure and includes novel method validation procedures that can accurately estimate the data obtained in measurements. It also enables the reader to provide practical insights to improve decision making by accurately evaluating and comparing different analytical methods. Brings together an interdisciplinary approach with statistical tools and algorithms applied in analytical chemistry and written by two international experts with long-standing experience in the field of Analytical measurements and Uncertainty, Quantification, Validation and Uncertainty in Analytical Sciences includes information on: The know-how of methods in an analytical laboratory, effective usage of a spurious measurement and methods to estimate errors. Quantification, calibration, precision, trueness, MAP addons, estimating MU for analytical sciences, and uncertainty functions Employing measurement uncertainty, sampling uncertainty, quantification limits, and sample conformity assessment Decision making, uncertainty and standard addition method, and accuracy profile for method comparison Quantification, Validation and Uncertainty in Analytical Sciences is an ideal resource for every individual quantifying or studying analytes. With several chapters dedicated to MU’s practical use in decision making demonstrating its advantages, the book is primarily intended for professional analysts, although researchers and students will also find it of interest.
Analytical Measurement
Author: Ricardo Bettencourt da Silva
Publisher:
Published: 2012
Total Pages: 237
ISBN-13: 9789279230714
DOWNLOAD EBOOK"TrainMiC® is a European programme for lifelong learning on how to interpret the metrological requirements in chemistry. It is operational across many parts of Europe via national teams. These teams use shareware pedagogic tools which have been harmonised at European level through the joint effort of many experts across Europe working as an editorial board. The material has been translated into 14 different languages. This report includes four TrainMiC® presentations."--Editor.
Measurement Uncertainty
Author: Simona Salicone
Publisher: Springer Science & Business Media
Published: 2007-06-04
Total Pages: 235
ISBN-13: 0387463283
DOWNLOAD EBOOKThe expression of uncertainty in measurement poses a challenge since it involves physical, mathematical, and philosophical issues. This problem is intensified by the limitations of the probabilistic approach used by the current standard (the GUM Instrumentation Standard). This text presents an alternative approach. It makes full use of the mathematical theory of evidence to express the uncertainty in measurements. Coverage provides an overview of the current standard, then pinpoints and constructively resolves its limitations. Numerous examples throughout help explain the book’s unique approach.
Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results (rev. Ed. )
Author: Barry N. Taylor
Publisher: DIANE Publishing
Published: 2009-11
Total Pages: 25
ISBN-13: 1437915566
DOWNLOAD EBOOKResults of measurements and conclusions derived from them constitute much of the technical information produced by the National Institute of Standards and Technology (NIST). In July 1992 the Director of NIST appointed an Ad Hoc Committee on Uncertainty Statements and charged it with recommending a policy on this important topic. The Committee concluded that the CIPM approach could be used to provide quantitative expression of measurement that would satisfy NIST¿s customers¿ requirements. NIST initially published a Technical Note on this issue in Jan. 1993. This 1994 edition addresses the most important questions raised by recipients concerning some of the points it addressed and some it did not. Illustrations.
An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
Author: Luis Tenorio
Publisher: SIAM
Published: 2017-07-06
Total Pages: 275
ISBN-13: 1611974917
DOWNLOAD EBOOKInverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.
