Ted Hill, Georgia Tech and Cal Poly SLO.
A century-old empirical observation now called Benford's Law says that the significant digits of many real datasets are logarithmically distributed, rather than uniformly distributed, as might be expected. New discoveries show that geometric Brownian motion (hence the stock market), and many algorithms including Newton's method also follow Benford's Law. This talk will briefly survey some of the colorful history of the problem, and applications to fraud detection, analysis of running times of algorithms, and diagnostic tests for mathematical models. The talk will include graphical heuristics, examples and open problems, and will be aimed for the non-specialist.
Archived event: In Windows Media Player
Posted by bayleyw at November 8, 2007 09:53 AM