Experimental Uncertainty Analysis: Mathematical model, Accuracy and precision, Random variable, Propagation of uncertainty, Uncertainty analysis, Taylor series, Systematic error, Sample size - Couverture souple

 
9786130253127: Experimental Uncertainty Analysis: Mathematical model, Accuracy and precision, Random variable, Propagation of uncertainty, Uncertainty analysis, Taylor series, Systematic error, Sample size
Couverture souple
ISBN 10 : 6130253125 ISBN 13 : 9786130253127
Editeur : Alphascript Publishing, 2009

Synopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The purpose of this introductory article is to discuss the experimental uncertainty analysis of a derived quantity, based on the uncertainties in the experimentally measured quantities that are used in some form of mathematical relationship ("model") to calculate that derived quantity. The model used to convert the measurements into the derived quantity is usually based on fundamental principles of a science or engineering discipline. The uncertainty has two components, namely, bias (related to accuracy) and the unavoidable random variation that occurs when making repeated measurements (related to precision). The measured quantities may have biases, and they certainly have random variation, so that what needs to be addressed is how these are "propagated" into the uncertainty of the derived quantity. Uncertainty analysis is often called the "propagation of error." It will be seen that this is a difficult and in fact sometimes intractable problem when handled in detail. Fortunately, approximate solutions are available that provide very useful results, and these approximations will be discussed in the context of a practical experimental example.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The purpose of this introductory article is to discuss the experimental uncertainty analysis of a derived quantity, based on the uncertainties in the experimentally measured quantities that are used in some form of mathematical relationship ("model") to calculate that derived quantity. The model used to convert the measurements into the derived quantity is usually based on fundamental principles of a science or engineering discipline. The uncertainty has two components, namely, bias (related to accuracy) and the unavoidable random variation that occurs when making repeated measurements (related to precision). The measured quantities may have biases, and they certainly have random variation, so that what needs to be addressed is how these are "propagated" into the uncertainty of the derived quantity. Uncertainty analysis is often called the "propagation of error." It will be seen that this is a difficult and in fact sometimes intractable problem when handled in detail. Fortunately, approximate solutions are available that provide very useful results, and these approximations will be discussed in the context of a practical experimental example.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Alphascript Publishing
Date d'édition
2009
Langue
anglais
ISBN 10 
6130253125
ISBN 13 
9786130253127
Reliure
Broché
Nombre de pages
68
Éditeur
Miller Frederic P., Vandome Agnes F., McBrewster John
Coordonnées du fabricant
non disponible
Personne responsable
non disponible