'I'll hazard my ring for this wench!' Masquerading as a serving girl to help her brother Julian find missing jewels, Susannah is infuriated by Lord Chalford's bet. Though she escapes him, when Susannah again meets Lord Chalford, she finds that he possesses some of those jewels--and that his father was present when Julian's father died in suspicious circumstances. Regency Romance by Sally James; originally published by Hale [London]

This book is about a history of the vice in ancient and modern times all over the world and makes an exposition of its alarming prevalence and destructive effects. This work discusses with an unreserved and exhaustive disclosure of such frauds, tricks and devices as are practiced by "Professional" gamblers, "Confidence Men" and "Bunko Steerers", in order to alert readers not to fall into a trap.

In 1956, two Bell Labs scientists discovered the scientific formula for getting rich. One was mathematician Claude Shannon, neurotic father of our digital age, whose genius is ranked with Einstein's. The other was John L. Kelly Jr., a Texas-born, gun-toting physicist. Together they applied the science of information theory—the basis of computers and the Internet—to the problem of making as much money as possible, as fast as possible. Shannon and MIT mathematician Edward O. Thorp took the "Kelly formula" to Las Vegas. It worked. They realized that there was even more money to be made in the stock market. Thorp used the Kelly system with his phenomenally successful hedge fund, Princeton-Newport Partners. Shannon became a successful investor, too, topping even Warren Buffett's rate of return. Fortune's Formula traces how the Kelly formula sparked controversy even as it made fortunes at racetracks, casinos, and trading desks. It reveals the dark side of this alluring scheme, which is founded on exploiting an insider's edge. Shannon believed it was possible for a smart investor to beat the market—and William Poundstone's Fortune's Formula will convince you that he was right.

Students and teachers of mathematics and related fields will find this book a comprehensive and modern approach to probability theory, providing the background and techniques to go from the beginning graduate level to the point of specialization in research areas of current interest. The book is designed for a two- or three-semester course, assuming only courses in undergraduate real analysis or rigorous advanced calculus, and some elementary linear algebra. A variety of applications—Bayesian statistics, financial mathematics, information theory, tomography, and signal processing—appear as threads to both enhance the understanding of the relevant mathematics and motivate students whose main interests are outside of pure areas.