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Détail de l'auteur
Auteur Ifan G. Hughes
Documents disponibles écrits par cet auteur
Faire une suggestion Affiner la rechercheMeasurements and their uncertainties / Ifan G. Hughes
Titre : Measurements and their uncertainties : a pratical guide to modern error analysis Type de document : texte imprimé Auteurs : Ifan G. Hughes, Auteur ; Thomas P.A. Hase, Auteur Editeur : Oxford : Oxford university press Année de publication : 2010 Importance : XIII, 136 p. Présentation : ill. Format : 25 cm ISBN/ISSN/EAN : 978-0-19-956632-7 Langues : Anglais (eng) Mots-clés : Erreurs de mesure (statistique mathématique)
Tests d'hypothèsesIndex. décimale : 519.233.3 Test d'hypothèse. Critères. Discrimination Résumé : 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. Note de contenu : In summary :
1. Errors in the physical sciences.
2. Random errors in measurement.
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 summary.Measurements and their uncertainties : a pratical guide to modern error analysis [texte imprimé] / Ifan G. Hughes, Auteur ; Thomas P.A. Hase, Auteur . - Oxford : Oxford university press, 2010 . - XIII, 136 p. : ill. ; 25 cm.
ISBN : 978-0-19-956632-7
Langues : Anglais (eng)
Mots-clés : Erreurs de mesure (statistique mathématique)
Tests d'hypothèsesIndex. décimale : 519.233.3 Test d'hypothèse. Critères. Discrimination Résumé : 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. Note de contenu : In summary :
1. Errors in the physical sciences.
2. Random errors in measurement.
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 summary.Exemplaires
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