Measurement theory for engineers

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The material in this book was initially presented as a graduate course in Measurement Theory for M. Sc. students at Ben Gurion University during the 2000/2001 academic year. It focuses on the statistical analysis of data from measurement processes, emphasizing general issues in processing measurement data rather than specific measurement techniques. The text does not delve into how to measure particular physical parameters, such as ohmic resistance or temperature, nor does it analyze the accuracy of specific measurement devices. The Introduction (Chapter 1) provides a concise overview of the measurement process, defines the measurand, and outlines various types of measurement errors. Chapter 2 covers point and interval estimation of population mean and standard deviation (variance), discussing normal and uniform distributions, which are the most commonly used in measurement contexts. It also reviews fundamental rules for handling means and variances of sums of random variables, crucial for integrating measurement results from diverse sources. Additionally, this chapter includes a brief overview of graphical tools for sample data analysis and presents round-off rules for data presentation.