Evaluating Measurement Accuracy: A Practical Approach
“Evaluating Measurement Accuracy, 2nd Edition” is intended for those who are concerned with measurements in any field of science or technology. It reflects the latest developments in metrology and offers new results, but is designed to be accessible to readers at different levels: scientists who advance the field of metrology, engineers and experimental scientists who use measurements as tool in their professions, students and graduate students in natural sciences and engineering, and, in parts describing practical recommendations, technicians performing mass measurements in industry, quality control, and trade. This book presents material from the practical perspective and offers solutions and recommendations for problems that arise in conducting real-life measurements.
This new edition adds a method for estimating accuracy of indirect measurements with independent arguments, whose development Dr. Rabinovich was able to complete very recently. This method, which is called the Method of Enumeration, produces estimates that are no longer approximate, similar to the way the method of reduction described in the first edition removed approximation in estimating uncertainty of indirect measurements with dependent arguments. The method of enumeration completes addressing the range of problems whose solutions signify the emergence of the new theory of accuracy of measurements. A new method is added for building a composition of histograms, and this method forms a theoretical basis for the method of enumeration.Additionally, as a companion to this book, a concise practical guide that assembles simple step-by-step procedures for typical tasks the practitioners are likely to encounter in measurement accuracy estimation is available at SpringerLink.
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Measuring Instruments and Their Properties
Statistical Methods for Experimental Data Processing
Combined and Simultaneous Measurements
Combining the Results of Measurements
Examples of Measurements and Measurement Data Processing
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absolutely constant error additional errors arguments arithmetic mean assume calculated combined components compute conditional equations conditionally constant errors confidence interval confidence probability corresponding degree of freedom determined digit distribution function elementary errors equal example experimental data expressed fiducial error formula given independent indirect measurements indication influence quantity intrinsic error limits of error limits of permissible linear measurand measured quantity measurement data measurement equation measurement error measurement result measurement standard measuring instruments metrology Monte Carlo method multiple measurements normal distribution number of measurements obtained output group parameters performed permissible error potentiometer problem quantile random errors random quantity reference conditions relative error relative form resistor results of measurements sample Sect single measurements Springer Science+Business Media standard deviation Student’s distribution systematic errors Table Taylor series temperature term traditional method true value variance voltage voltmeter weighted mean α ¼ θα