Probably Not: Future Prediction Using Probability and Statistical Inference
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An engaging, entertaining, and informative introduction to probability and prediction in our everyday lives
Although Probably Not deals with probability and statistics, it is not heavily mathematical and is not filled with complex derivations, proofs, and theoretical problem sets. This book unveils the world of statistics through questions such as what is known based upon the information at hand and what can be expected to happen. While learning essential concepts including "the confidence factor" and "random walks," readers will be entertained and intrigued as they move from chapter to chapter. Moreover, the author provides a foundation of basic principles to guide decision making in almost all facets of life including playing games, developing winning business strategies, and managing personal finances.
Much of the book is organized around easy-to-follow examples that address common, everyday issues such as:
*How travel time is affected by congestion, driving speed, and traffic lights
*Why different gambling casino strategies ultimately offer players no advantage
*How to estimate how many different birds of one species are seen on a walk through the woods
Seemingly random events—coin flip games, the Central Limit Theorem, binomial distributions and Poisson distributions, Parrando's Paradox, and Benford's Law—are addressed and treated through key concepts and methods in probability. In addition, fun-to-solve problems including "the shared birthday" and "the prize behind door number one, two, or three" are found throughout the book, which allow readers to test and practice their new probability skills. Requiring little background knowledge of mathematics, readers will gain a greater understanding of the many daily activities and events that involve random processes and statistics.
Combining the mathematics of probability with real-world examples, Probably Not is an ideal reference for practitioners and students who would like to learn more about the role of probability and statistics in everyday decision making.
Lawrence N. Dworsky, PhD, is a former corporate research lab director at Motorola, Inc., where he was also a member of the Science Advisory Board. He has also served as a consultant to the Defense Advanced Research Projects Agency (DARPA), Littelfuse Corp., and HRL Laboratories, LLC. A Fellow of the Institute of Electrical and Electronic Engineers, Dr. Dworsky has held academic positions at Columbia University, Northern Illinois University, and Florida Atlantic University.
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