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Measurements and their uncertainties : a practical guide to modern error analysis / Ifan G. Hughes, Thomas P.A. Hase.

By: Contributor(s): Material type: TextTextPublisher: Oxford ; New York : Oxford University Press, 2010Description: 1 online resource (xiii, 136 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780191576560
  • 0191576565
  • 9780199566334
  • 019956633X
  • 128273234X
  • 9781282732346
  • 9786612732348
  • 6612732342
Subject(s): Genre/Form: Additional physical formats: Print version:: Measurements and their uncertainties.DDC classification:
  • 511/.43 22
LOC classification:
  • QA275 .H84 2010eb
Online resources:
Contents:
1 Errors in the physical sciences; 2 Random errors in measurements; 3 Uncertainties as probabilities; 4 Error propagation; 5 Data visualisation and reduction; 6 Least-squares fitting of complex functions; 7 Computer minimisation and the error matrix; 8 Hypothesis testing -- how good are our models?; 9 Topics for further study; Bibliography; Index.
Summary: This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.
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Includes bibliographical references (pages 131-132) and index.

1 Errors in the physical sciences; 2 Random errors in measurements; 3 Uncertainties as probabilities; 4 Error propagation; 5 Data visualisation and reduction; 6 Least-squares fitting of complex functions; 7 Computer minimisation and the error matrix; 8 Hypothesis testing -- how good are our models?; 9 Topics for further study; Bibliography; Index.

This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.

Print version record.

English.

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