Probabilities The Little Numbers That Rule Our Lives

Praise for the First Edition If there is anything you want to know, or remind yourself, about probabilities, then look no further than this comprehensive, yet wittily written and enjoyable, compendium of how to apply probability calculations in real-world situations.

Praise for the First Edition

“If there is anything you want to know, or remind yourself, about probabilities, then look no further than this comprehensive, yet wittily written and enjoyable, compendium of how to apply probability calculations in real-world situations.”

- Keith Devlin, Stanford University, National Public Radio’s “Math Guy” and author of The Math Gene and The Unfinished Game

From probable improbabilities to regular irregularities, Probabilities: The Little Numbers That Rule Our Lives, Second Edition investigates the often surprising effects of risk and chance in our lives. Featuring a timely update, the Second Edition continues to be the go-to guidebook for an entertaining presentation on the mathematics of chance and uncertainty.

The new edition develops the fundamental mathematics of probability in a unique, clear, and informal way so readers with various levels of experience with probability can understand the little numbers found in everyday life. Illustrating the concepts of probability through relevant and engaging real-world applications, the Second Edition features numerous examples on weather forecasts, DNA evidence, games and gambling, and medical testing. The revised edition also includes:

• Applications of probability in finance, such as option pricing

• The introduction of branching processes and the extinction of family names

• An extended discussion on opinion polls and Nate Silver’s election predictions

Probabilities: The Little Numbers That Rule Our Lives, Second Edition is an ideal reference for anyone who would like to obtain a better understanding of the mathematics of chance, as well as a useful supplementary textbook for students in any course dealing with probability.

Peter Olofsson, PhD, is Professor in the Department of Mathematics at Trinity University, USA. An active researcher in the field of applied probability and an experienced teacher, Dr. Olofsson is the author of Probability, Statistics, and Stochastic Processes, Second Edition, also published by Wiley.

Praise for the First Edition

“If there is anything you want to know, or remind yourself, about probabilities, then look no further than this comprehensive, yet wittily written and enjoyable, compendium of how to apply probability calculations in real-world situations.”

- Keith Devlin, Stanford University, National Public Radio’s “Math Guy” and author of The Math Gene and The Unfinished Game

From probable improbabilities to regular irregularities, Probabilities: The Little Numbers That Rule Our Lives, Second Edition investigates the often surprising effects of risk and chance in our lives. Featuring a timely update, the Second Edition continues to be the go-to guidebook for an entertaining presentation on the mathematics of chance and uncertainty.

The new edition develops the fundamental mathematics of probability in a unique, clear, and informal way so readers with various levels of experience with probability can understand the little numbers found in everyday life. Illustrating the concepts of probability through relevant and engaging real-world applications, the Second Edition features numerous examples on weather forecasts, DNA evidence, games and gambling, and medical testing. The revised edition also includes:

• The application of probability in finance, such as option pricing
• The introduction of branching processes and the extinction of family names
• An extended discussion on opinion polls and Nate Silver’s election predictions

Probabilities: The Little Numbers That Rule Our Lives, Second Edition is an ideal reference for anyone who would like to obtain a better understanding of the mathematics of chance, as well as a useful supplementary textbook for students in any course dealing with probability.