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Measurement Uncertainty and Probability

$151.00 (C)

  • Date Published: March 2013
  • availability: In stock
  • format: Hardback
  • isbn: 9781107021938

$ 151.00 (C)
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About the Authors
  • 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.

    • Proposes a classical performance-based approach to the analysis of measurement error and uncertainty
    • Extends classical statistical principles in a way that fits the measurement context, giving intervals of measurement uncertainty a practical meaning
    • Distinguishes different statistical concepts and objects using notation and language
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    Product details

    • Date Published: March 2013
    • format: Hardback
    • isbn: 9781107021938
    • length: 291 pages
    • dimensions: 253 x 177 x 18 mm
    • weight: 0.74kg
    • contains: 43 b/w illus.
    • availability: In stock
  • Table of Contents

    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.

  • Author

    Robin Willink
    Robin Willink is a physicist-turned-statistician, who until recently worked for Applied Mathematics, Industrial Research Ltd, the parent body of the National Metrology Institute of New Zealand. His work on statistical methods for measurement is highly regarded.

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