Evaluating the Measurement Uncertainty is a book written for anyone who makes and reports measurements. It attempts to fill the gaps in the ISO Guide to the Expression of Uncertainty in Measurement, or the GUM, and does a pretty thorough job. The GUM was written with the intent of being applicable by all metrologists, from the shop floor to the National Metrology Institute laboratory; however, the GUM has often been criticized for its lack of user-friendliness because it is primarily filled with statements, but with little explanation. Evaluating the Measurement Uncertainty gives lots of explanations. It is well written and makes use of many good figures and numerical examples. Also important, this book is written by a metrologist from a National Metrology Institute, and therefore up-to-date ISO rules, style conventions and definitions are correctly used and supported throughout. The author sticks very closely to the GUM in topical theme and with frequent reference, so readers who have not read GUM cover-to-cover may feel as if they are missing something.

The first chapter consists of a reprinted lecture by T J Quinn, Director of the Bureau International des Poids et Mesures (BIPM), on the role of metrology in today's world. It is an interesting and informative essay that clearly outlines the importance of metrology in our modern society, and why accurate measurement capability, and by definition uncertainty evaluation, should be so important. Particularly interesting is the section on the need for accuracy rather than simply reproducibility.

Evaluating the Measurement Uncertainty then begins at the beginning, with basic concepts and definitions. The third chapter carefully introduces the concept of standard uncertainty and includes many derivations and discussion of probability density functions. The author also touches on Monte Carlo methods, calibration correction quantities, acceptance intervals or guardbanding, and many other interesting cases. The book goes on to treat evaluation of expanded uncertainty, joint treatment of several measurands, least-squares adjustment, curve fitting and more. Chapter 6 is devoted to Bayesian inference.

Perhaps one can say that Evaluating the Measurement Uncertainty caters to a wider reader-base than the GUM; however, a mathematical or statistical background is still advantageous. Also, this is not a book with a library of worked overall uncertainty evaluations for various measurements; the feel of the book is rather theoretical. The novice will still have some work to do—but this is a good place to start. I think this book is a fitting companion to the GUM because the text complements the GUM, from fundamental principles to more sophisticated measurement situations, and moreover includes intelligent discussion regarding intent and interpretation. Evaluating the Measurement Uncertainty is detailed, and I think most metrologists will really enjoy the detail and care put into this book.

Jennifer Decker, 2003 Metrologia 40 207

Editorial: IOP

Librerías: amazon.com