Uncertainty, Calibration and Probability

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Publisher :
ISBN 13 :
Total Pages : 438 pages
Book Rating : 4.08/5 ( download)

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Book Synopsis Uncertainty, Calibration and Probability by : Cornelius Frank Dietrich

Download or read book Uncertainty, Calibration and Probability written by Cornelius Frank Dietrich and published by . This book was released on 1973 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Uncertainty, Calibration and Probability

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Publisher : Routledge
ISBN 13 : 1351406272
Total Pages : 408 pages
Book Rating : 4.77/5 ( download)

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Book Synopsis Uncertainty, Calibration and Probability by : C.F Dietrich

Download or read book Uncertainty, Calibration and Probability written by C.F Dietrich and published by Routledge. This book was released on 2017-07-12 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: All measurements are subject to error because no quantity can be known exactly; hence, any measurement has a probability of lying within a certain range. The more precise the measurement, the smaller the range of uncertainty. Uncertainty, Calibration and Probability is a comprehensive treatment of the statistics and methods of estimating these calibration uncertainties. The book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also discusses sources of measurement errors and curve fitting with numerous examples of uncertainty case studies. Many useful tables and computational formulae are included as well. All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text. New chapters consist of the general theory of uncertainty and applications to industry and a new section discusses the use of orthogonal polynomials in curve fitting. Focusing on practical problems of measurement, Uncertainty, Calibration and Probability is an invaluable reference tool for R&D laboratories in the engineering/manufacturing industries and for undergraduate and graduate students in physics, engineering, and metrology.

Uncertainty, Calibration and Probability

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Publisher : CRC Press
ISBN 13 : 9780750300605
Total Pages : 564 pages
Book Rating : 4.04/5 ( download)

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Book Synopsis Uncertainty, Calibration and Probability by : C.F Dietrich

Download or read book Uncertainty, Calibration and Probability written by C.F Dietrich and published by CRC Press. This book was released on 1991-01-01 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: All measurements are subject to error because no quantity can be known exactly; hence, any measurement has a probability of lying within a certain range. The more precise the measurement, the smaller the range of uncertainty. Uncertainty, Calibration and Probability is a comprehensive treatment of the statistics and methods of estimating these calibration uncertainties. The book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also discusses sources of measurement errors and curve fitting with numerous examples of uncertainty case studies. Many useful tables and computational formulae are included as well. All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text. New chapters consist of the general theory of uncertainty and applications to industry and a new section discusses the use of orthogonal polynomials in curve fitting. Focusing on practical problems of measurement, Uncertainty, Calibration and Probability is an invaluable reference tool for R&D laboratories in the engineering/manufacturing industries and for undergraduate and graduate students in physics, engineering, and metrology.

Uncertainty, Calibration, and Probability

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Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 434 pages
Book Rating : 4.94/5 ( download)

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Book Synopsis Uncertainty, Calibration, and Probability by : Cornelius Frank Dietrich

Download or read book Uncertainty, Calibration, and Probability written by Cornelius Frank Dietrich and published by John Wiley & Sons. This book was released on 1973 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also describes sources of measurement errors and curve fitting with numerous examples of uncertainty case studies as well as useful tables and computational formulae. With additional examples in each chapter, this second edition includes new chapters on the general theory of uncertainty and applications to industry and a new section that discusses the use of orthogonal polynomials in curve fitting.

Measurement Uncertainties

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Publisher : Springer Science & Business Media
ISBN 13 : 3642209890
Total Pages : 336 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Measurement Uncertainties by : S. V. Gupta

Download or read book Measurement Uncertainties written by S. V. Gupta and published by Springer Science & Business Media. This book was released on 2012-01-13 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book fulfills the global need to evaluate measurement results along with the associated uncertainty. In the book, together with the details of uncertainty calculations for many physical parameters, probability distributions and their properties are discussed. Definitions of various terms are given and will help the practicing metrologists to grasp the subject. The book helps to establish international standards for the evaluation of the quality of raw data obtained from various laboratories for interpreting the results of various national metrology institutes in an international inter-comparisons. For the routine calibration of instruments, a new idea for the use of pooled variance is introduced. The uncertainty calculations are explained for (i) independent linear inputs, (ii) non-linear inputs and (iii) correlated inputs. The merits and limitations of the Guide to the Expression of Uncertainty in Measurement (GUM) are discussed. Monte Carlo methods for the derivation of the output distribution from the input distributions are introduced. The Bayesian alternative for calculation of expanded uncertainty is included. A large number of numerical examples is included.

Probability and Bayesian Modeling

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Publisher : CRC Press
ISBN 13 : 1351030132
Total Pages : 553 pages
Book Rating : 4.37/5 ( download)

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Book Synopsis Probability and Bayesian Modeling by : Jim Albert

Download or read book Probability and Bayesian Modeling written by Jim Albert and published by CRC Press. This book was released on 2019-12-06 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.

Measurement Uncertainty

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Publisher : ISA
ISBN 13 : 9781556179150
Total Pages : 292 pages
Book Rating : 4.54/5 ( download)

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Book Synopsis Measurement Uncertainty by : Ronald H. Dieck

Download or read book Measurement Uncertainty written by Ronald H. Dieck and published by ISA. This book was released on 2007 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Literally an entire course between two covers, Measurement Uncertainty: Methods and Applications, Fourth Edition, presents engineering students with a comprehensive tutorial of measurement uncertainty methods in a logically categorized and readily utilized format. The new uncertainty technologies embodied in both U.S. and international standards have been incorporated into this text with a view toward understanding the strengths and weaknesses of both. The book is designed to also serve as a practical desk reference in situations that commonly confront an experimenter. The text presents the basics of the measurement uncertainty model, non-symmetrical systematic standard uncertainties, random standard uncertainties, the use of correlation, curve-fitting problems, and probability plotting, combining results from different test methods, calibration errors, and uncertainty propagation for both independent and dependent error sources. The author draws on years of experience in industry to direct special attention to the problem of developing confidence in uncertainty analysis results and using measurement uncertainty to select instrumentation systems.

Measurement Uncertainty and Probability

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Publisher :
ISBN 13 : 9781139616188
Total Pages : 276 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Measurement Uncertainty and Probability by : Robin Willink

Download or read book Measurement Uncertainty and Probability written by Robin Willink and published by . This book was released on 2013 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science"--

Measurement Uncertainty

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Publisher : Springer Science & Business Media
ISBN 13 : 0387463283
Total Pages : 235 pages
Book Rating : 4.85/5 ( download)

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Book Synopsis Measurement Uncertainty by : Simona Salicone

Download or read book Measurement Uncertainty written by Simona Salicone and published by Springer Science & Business Media. This book was released on 2007-06-04 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 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.

Measurement Uncertainty and Probability

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Publisher : Cambridge University Press
ISBN 13 : 113961990X
Total Pages : 295 pages
Book Rating : 4.05/5 ( download)

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Book Synopsis Measurement Uncertainty and Probability by : Robin Willink

Download or read book Measurement Uncertainty and Probability written by Robin Willink and published by Cambridge University Press. This book was released on 2013-02-14 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.