Measurement Uncertainty and Probability

Useful for researchers and graduate students, this book examines the practical meaning of probability.

Robin Willink (Author)

9781107021938, Cambridge University Press

Hardback, published 14 February 2013

291 pages, 43 b/w illus.
25.3 x 17.7 x 1.8 cm, 0.74 kg

A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.

Part I. Principles: 1. Introduction
2. Foundational ideas in measurement
3. Components of error or uncertainty
4. Foundational ideas in probability and statistics
5. The randomization of systematic errors
6. Beyond the standard confidence interval
Part II. Evaluation of Uncertainty: 7. Final preparation
8. Evaluation using the linear approximation
9. Evaluation without the linear approximations
10. Uncertainty information fit for purpose
Part III. Related Topics: 11. Measurement of vectors and functions
12. Why take part in a measurement comparison?
13. Other philosophies
14. An assessment of objective Bayesian methods
15. A guide to the expression of uncertainty in measurement
16. Measurement near a limit – an insoluble problem?
References
Index.

Subject Areas: Technology, engineering, agriculture [T], Physics [PH], Mathematics & science [P]