10 best measurement uncertainty for 2019
Finding your suitable measurement uncertainty is not easy. You may need consider between hundred or thousand products from many store. In this article, we make a short list of the best measurement uncertainty including detail information and customer reviews. Let’s find out which is your favorite one.
Best measurement uncertainty
1. Introduction to Error Analysis: The Science of Measurements, Uncertainties, and Data Analysis
Description
Great scientists master the math behind the science.
Do you still delay mastering data analysis, keeping you from more accurate, rigorous, and higher certainty conclusions?
Jack Merrin, Ph.D. Princeton University, is a physicist who has helped hundreds of students with math and physics, taught physics labs, and used error analysis through 25 years of research. You can surely learn the right statistical methods from Jack.
Introduction to Error Analysis is more than a collection of ad-hoc statistical theory. It is an easy-to-read blueprint used by scientists for presenting correct results. Transform your experimental perspective to confidence. Learn reusable principles for each new scientific project. This book covers reporting measurements and uncertainties, propagation of error, combining results, curve fitting, essential statistical concepts, and much, much, more.
You might love this book if:
- You are doing lab reports or actual research, and it's time to get serious about data analysis.
- You want to focus on the essential calculations, not on time-wasting theory.
- You want adaptable MATLAB code for each different calculation. Hey, no need to reinvent the wheel.
- You want to reach correct and unique results using the established convention.
- You want to know what is correct to spot bad scientific literature.
Introduction to Error Analysis is the concise book you need to start building your successful scientific career. If you like easy-to-follow lessons, practical examples, insightful tips, and an author who actually cares about you getting it right, then youll love Jack's book.
Buy Introduction to Error Analysis to start refining your data analysis skills today!
2. Measurement Uncertainty: Methods and Applications, Fifth Edition
Description
This fifth edition of Measurement Uncertainty: Methods and Applications is designed to provide an understanding of the importance of the roleplayed by measurement uncertainty analysis in any test or experimental measurement process. No test data should be considered without knowing their uncertainty. Examples and problems have been included to illustrate the principles and applications of measurement uncertainty analysis. Sections on the business impact of measurement uncertainty and the treatment of calibration uncertainty have been included. The very latest in measurement uncertainty technology is included in this revised edition. In addition, all the material herein is in full harmony with the ISO Guide to the Expression of Uncertainty in Measurement. Specifically, the terminology and symbols are in agreement with the U.S. National Standard on Test Uncertainty and in harmony with the ISO Guide. The term standard uncertainty is employed throughout to indicate that each uncertainty mentioned is one standard deviation of the average for a group of measurements. Thus, instead of reporting random uncertainty and systematic uncertainty, this text now uses
the terms random standard uncertainty and systematic standard uncertainty. This material will be useful to test engineers, process engineers, control engineers, researchers, plant supervisors, managers, executives, and all others who need a basic understanding of the assessment and impact of uncertainty in test and experimental measurements. In addition, technical school, college, and university students will find this course useful in gaining insight into the impact of errors in their measurements, as well as estimating the effects of such errors with measurement uncertainty analysis.
3. Measurements and their Uncertainties: A practical guide to modern error analysis
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Oxford University Press USADescription
This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory.Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.
4. The History of Statistics: The Measurement of Uncertainty before 1900
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Used Book in Good ConditionDescription
This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900. Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing questions: How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galtons probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century?
Stiglers emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantitative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs.
Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.
5. Measurement Uncertainty in Forensic Science: A Practical Guide
Description
In the courtroom, critical and life-changing decisions are made based on quantitative forensic science data. There is often a range in which a measured value is expected to fall and, in this, an inherent uncertainty associated with such measurement. Uncertainty in this context is not error. In fact, estimations of uncertainty can add to the utility and reliability of quantitative results, be it the length of a firearm barrel, the weight of a drug sample, or the concentration of ethanol in blood.
Measurement Uncertainty in Forensic Science: A Practical Guide describes and defines the concepts related to such uncertainty in the forensic context. The book provides the necessary conceptual background and frameworka baselinefor developing and deploying reasonable and defensible uncertainty estimations across forensic disciplines. Information is presented conceptually, using easily understood examples, to provide a readable, handy reference for scientists in the laboratory, as well as investigators and legal professionals who require a basic understanding of the science underpinning measurement results.
6. Uncertainty of Measurements: Physical and Chemical Metrology: Impact & Analysis
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Used Book in Good ConditionDescription
With the uncertainly of measurement results drawing the attention of managers, metrologists, and customers, this comprehensive guide works to show the importance of metrology while explaining the science of the uncertainty of measurements. Kimothi shows how the accuracy of measurements affects all of us in trade, commerce, safety, health care, environmental protection, and more. External and internal customers, along with regulatory agencies, often prescribe measurement accuracy requirements. This book helps to sort out the current issues surrounding measurement reliability. Kimothi's explanations make it easier for organizations to understand the concerns of measurement uncertainty in decision-making.Newcomers to metrology will find Kimothi's explanations easy to follow because this book starts off with a comprehensive introduction to the basic principles of reliable measurements. As the text progresses, these basic principles provide a foundation for more and more advanced aspects of measurement uncertainty. The book describes: the need for measurement certainty, techniques to achieve results, and standards in measurement. This comprehensive range of information makes this an ideal desk reference for metrology students and statistical quality enthusiasts. Kimothi includes information about current events regarding reliable measurements and how the uncertainty of measurements affects trade, Six Sigma, and more.
Topics covered include:
Guide to the Expression of Uncertainty in Measurement (GUM) approach
A complete chapter on calibration and measurement traceability
Statistical techniques in metrology
Examples of measurement data and random variables
Probability density functions
Sampling distribution
Statistical estimation degrees of freedom and regression
How to evaluate various uncertainties in measurements using several approaches including international consensus
One chapter is devoted to measurement errors
Information specific to calibration laboratories
Examples of R&R studies
7. An Introduction to Uncertainty in Measurement: Using The Gum (Guide To The Expression Of Uncertainty In Measurement)
Description
Measurement 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/9780521605793.8. Evaluating the Measurement Uncertainty: Fundamentals and Practical Guidance (Series in Measurement Science and Technology)
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Used Book in Good ConditionDescription
It is now widely recognized that measurement data should be properly analyzed to include an assessment of their associated uncertainty. Since this parameter allows for a meaningful comparison of the measurement results and for an evaluation of their reliability, its expression is important not only in the specialized field of scientific metrology, but also in industry, trade, and commerce. General rules for evaluating and expressing the uncertainty are given in the internationally accepted ISO Guide to the Expression of Uncertainty in Measurement, generally known as the GUM.Evaluating the Measurement Uncertainty details the theoretical framework on which the GUM is based and provides additional material on more advanced topics such as least-squares adjustment and Bayesian statistics. The book does not require previous knowledge other than elementary calculus and can be read as a complement to the GUM or as a stand-alone reference source. It stresses fundamental principles and illustrates their applications through numerous examples taken from many different fields of metrology. The book includes practical guidance as well as theoretical aspects, resulting in an invaluable resource for metrologists, engineers, physicists, and graduate students involved with measurements in academia and industry.
9. Calculating measurement uncertainties
10. An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements
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