Measurements and their Uncertainties : A practical guide to modern error analysis
Book Details
Format
Paperback / 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
22.40 x 21.50 x 2.80 cms
Product Classification:
Calculus of variations Mensuration & systems of measurement Statistical physics Mathematical physics
Ksh 5,150.00
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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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