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

Students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces the internationally recognised and recommended guidelines for calculating and expressing uncertainty (the GUM) to students and professionals in science and engineering. The role of uncertainty is emphasised in scientific and 'everyday' contexts, and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments reinforce the principles described within and online resources support the book at www.cambridge.org/9780521605793.

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.

Introduction to international guidelines for calculating and expressing uncertainty (the GUM) for students and professionals in science and engineering. Emphasising the role of uncertainty in scientific and 'everyday' contexts, worked examples, case studies and exercises are spread throughout the text. Online resources support the book at www.cambridge.org/9780521605793.

Les Kirkup is Associate Professor in the School of Physics and Advanced Materials, University of Technology, Sydney. A dedicated lecturer, many of his educational developments have focused on enhancing the laboratory experience of undergraduate students. In May 2011, he was awarded an Australian Learning and Teaching Council National Teaching Fellowship.
Bob Frenkel is a senior experimental scientist at the Australian National Measurement Institute.