Benford's Law : Theory and Applications
Benford s law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths...
Gespeichert in:
| Weitere Verfasser: | |
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| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Princeton, N.J. :
Princeton University Press
[2015].
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| Ausgabe: | Course Book. |
| Schlagworte: | |
| Online Zugang: | Accès Université d'Orléans et IFPM Accès INSA CVL |
| Anmerkung: |
MillerSteven J.: Steven J. Miller is associate professor of mathematics at Williams College. He is the coauthor of An Invitation to Modern Number Theory (Princeton) Description based on online resource; title from PDF title page (publisher's Web site, viewed September 10 2015) La pagination de l'édition imprimée correspondante est de : 464 p. Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur |
| Autres localisations: | Voir dans le Sudoc |
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| 041 | 0 | |a eng | |
| 082 | |a 519.2/4 | ||
| 084 | |a 519.2/4 | ||
| 245 | 1 | 0 | |a Benford's Law : |b Theory and Applications |c edited by Steven J. Miller. |
| 250 | |a Course Book. | ||
| 256 | |a Données textuelles | ||
| 260 | |a Princeton, N.J. : |b Princeton University Press, |c [2015]. | ||
| 500 | |a MillerSteven J.: Steven J. Miller is associate professor of mathematics at Williams College. He is the coauthor of An Invitation to Modern Number Theory (Princeton) | ||
| 500 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed September 10 2015) | ||
| 500 | |a La pagination de l'édition imprimée correspondante est de : 464 p. | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur | ||
| 506 | |a L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition | ||
| 520 | |a Benford s law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths of rivers. Here, Steven Miller brings together many of the world s leading experts on Benford s law to demonstrate the many useful techniques that arise from the law, show how truly multidisciplinary it is, and encourage collaboration.Beginning with the general theory, the contributors explain the prevalence of the bias, highlighting explanations for when systems should and should not follow Benford s law and how quickly such behavior sets in. They go on to discuss important applications in disciplines ranging from accounting and economics to psychology and the natural sciences. The contributors describe how Benford s law has been successfully used to expose fraud in elections, medical tests, tax filings, and financial reports. Additionally, numerous problems, background materials, and technical details are available online to help instructors create courses around the book.Emphasizing common challenges and techniques across the disciplines, this accessible book shows how Benford s law can serve as a productive meeting ground for researchers and practitioners in diverse fields | ||
| 533 | |n Reproduction électronique. Princeton, N.J. : Princeton University Press, 2015. Mode d'accès : Internet. System requirements: Web browser. Access may be restricted to users at subscribing institutions. | ||
| 538 | |a Nécessite un navigateur et un lecteur de fichier PDF | ||
| 650 | |a MATHEMATICS |x Applied | ||
| 650 | |a Mathematics |x Probability & Statistics |x General | ||
| 650 | |a Distribution (théorie des probabilités) | ||
| 650 | |a Mesures de probabilités | ||
| 700 | 1 | |a Miller, Steven J. |4 edt | |
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