An Introduction to Uncertainty in Measurement
Using the GUM (Guide to the Expression of Uncertainty in Measurement)

A guide to international guidelines for calculating and expressing uncertainty, for students and professionals in science/engineering.

L. Kirkup (Author), R. B. Frenkel (Author)

9780521605793, Cambridge University Press

Paperback, published 1 June 2006

248 pages, 100 b/w illus. 30 tables 35 exercises
24.4 x 17 x 1.3 cm, 0.5 kg

'…remarkably concise and very readable textbook… Many worked examples, a series of set problems with answers, numerous footnotes that expand upon the material covered, and a helpful index also play their part in making this a very useful book for undergraduates.' Chemistry World

Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.

Preface
1. The importance of uncertainty in science and technology
2. Measurement fundamentals
3. Terms used in measurement
4. Introduction to uncertainty in measurement
5. Some statistical concepts
6. Systematic errors
7. Calculation of uncertainties
8. Probability density, the Gaussian distribution and the Central Limit Theorem
9. Sampling a Gaussian distribution
10. The t-distribution, and the Welch–Satterthwaite formula
11. Case studies in measurement uncertainty
Appendices
References
Index.

Subject Areas: Earth sciences [RB], Biology, life sciences [PS], Chemistry [PN], Physics [PH], Astronomy, space & time [PG], Science: general issues [PD], Mathematics [PB]