Measurement Theory for Engineers

1. Front Matter

   Pages i-xiii

   PDF

2. Introduction: Measurand and Measurement Errors

   • Ilya Gertsbakh

   Pages 1-8

3. Measuring Population Mean and Standard Deviation

   • Ilya Gertsbakh

   Pages 9-41

4. Comparing Means and Variances

   • Ilya Gertsbakh

   Pages 43-58

5. Sources of Uncertainty: Process and Measurement Variability

   • Ilya Gertsbakh

   Pages 59-85

6. Measurement Uncertainty: Error Propagation Formula

   • Ilya Gertsbakh

   Pages 87-94

7. Calibration of Measurement Instruments

   • Ilya Gertsbakh

   Pages 95-112

8. Collaborative Studies

   • Ilya Gertsbakh

   Pages 113-122

9. Measurements in Special Circumstances

   • Ilya Gertsbakh

   Pages 123-132

10. Back Matter

    Pages 133-150

    PDF

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.

• Measure
• Normal
• Normal distribution
• calibration curves
• data analysis
• error propagation
• industrial
• measurement errors
• processes
• production
• quality
• random-effects ANOVA
• round-off errors
• static
• statistics
• quality control, reliability, safety and risk

From the reviews:

"This textbook deals with the principal issues of measurement theory. Each topic starts with an informal introduction followed by an example, the rigorous problem formulation, solution method, and a detailed numerical solution. … This book is intended as a text for graduate students and a reference for researchers and industrial experts specializing in measurement data analysis for quality control and industrial process improvement." (Ivan Krivý, Zentralblatt MATH, Vol. 1018, 2003)

• Department of Mathematics, Ben Gurion University of the Negev, Beer-Sheva, Israel

  Ilya Gertsbakh

Policies and ethics