Measurement Uncertainty and Probability
eBook - PDF

Measurement Uncertainty and Probability

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Measurement Uncertainty and Probability

About this book

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.

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Yes, you can access Measurement Uncertainty and Probability by Robin Willink in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Physics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Contents
  3. Acknowledgements
  4. Introduction
  5. Part I Principles
  6. Part II Evaluation of uncertainty
  7. Part III Related topics
  8. Appendix A The weak law of large numbers
  9. Appendix B The Sleeping Beauty paradox
  10. Appendix C The sum of normal and uniform variates
  11. Appendix D Analysis with one Type A and one Type B error
  12. Appendix E Conservatism of treatment of Type A errors
  13. Appendix F An alternative to a symmetric beta distribution
  14. Appendix G Dimensions of the ellipsoidal confidence region
  15. Appendix H Derivation of the Feldman–Cousins interval
  16. References
  17. Index