Measurement Theory for Engineers (eBook, PDF)
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The material in this book was first presented as a one-semester graduate course in Measurement Theory for M.Sc. students of the Industrial Engineering De partment of Ben Gurion University in the 2000/2001 academic year. The book is devoted to various aspects of the statistical analysis of data arising in the process of measurement. We would like to stress that the book is devoted to general problems arising in processing measurement data and does not deal with various aspects of special measurement techniques. For example, we do not go into the details of how special physical parameters, say o...
The material in this book was first presented as a one-semester graduate course in Measurement Theory for M.Sc. students of the Industrial Engineering De partment of Ben Gurion University in the 2000/2001 academic year. The book is devoted to various aspects of the statistical analysis of data arising in the process of measurement. We would like to stress that the book is devoted to general problems arising in processing measurement data and does not deal with various aspects of special measurement techniques. For example, we do not go into the details of how special physical parameters, say ohmic resistance or temperature, should be measured. We also omit the accuracy analysis of particular measurement devices. The Introduction (Chapter 1) gives a general and brief description of the measurement process, defines the measurand and describes different kinds of the measurement error. Chapter 2 is devoted to the point and interval estimation of the popula tion mean and standard deviation (variance). It also discusses the normal and uniform distributions, the two most widely used distributions in measurement. We give an overview of the basic rules for operating with means and variances of sums of random variables. This information is particularly important for combining measurement results obtained from different sources. There is a brief description of graphical tools for analyzing sampIe data. This chapter also presents the round-off rules for data presentation.
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