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Measurements and their Uncertainties : A practical guide to modern error analysis

By: (Author) Ifan Hughes , (Author) Thomas Hase

Extended Catalogue

Ksh 5,150.00

Format: Paperback or Softback

ISBN-10: 019956633X

ISBN-13: 9780199566334

Publisher: Oxford University Press

Imprint: Oxford University Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jul 1st, 2010

Print length: 160 Pages

Weight: 356 grams

Dimensions (height x width x thickness): 22.40 x 21.50 x 2.80 cms

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This short guide to modern error analysis is primarily intended to be used in undergraduate laboratories in the physical sciences. No prior knowledge of statistics is assumed. The necessary concepts are introduced where needed and illustrated graphically. The book emphasises the use of computers for error calculations and data fitting.
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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