* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Benford's Law
Steven J. Miller (Hrsg.)
* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Naturwissenschaften, Medizin, Informatik, Technik / Mathematik
Beschreibung
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.
Kundenbewertungen
Jeffreys prior, Accuracy and precision, Error, For All Practical Purposes, Linear regression, Empirical likelihood, Bayesian statistics, Central limit theorem, Geometric Brownian motion, Normal distribution, Significant figures, Hyperparameter, Logarithm, Logarithmic distribution, Rounding, Martingale (probability theory), Bayesian, Locally integrable function, Data set, Chi-squared test, Hypergeometric distribution, Maximum entropy probability distribution, Azuma's inequality, Proportionality (mathematics), Scale invariance, Closure (mathematics), Fair coin, Heaviside step function, Sign (mathematics), Summary statistics, Probability measure, Riemann zeta function, Arbitrarily large, Statistic, Antiderivative, Roth's theorem, Pearson's chi-squared test, Result, Big O notation, Convolution theorem, Rate of convergence, Exponential function, Nonparametric regression, Natural logarithm, Probability distribution, Uniform distribution (discrete), Benford's law, Infimum and supremum, Frank Benford, Kronecker delta, Euler's formula, Random sequence, Maximum likelihood estimation, Zipf's law, Generalized method of moments, Length scale, Upper and lower bounds, Lychrel number, Newton's method, Ordinary least squares, Beta distribution, Concentration of measure, Fraud, Cumulative distribution function, Infinite product, Joint probability distribution, Coefficient, Probability, Lucky number, Random variable