Practical tips for solving probability problems. Increase your chances of acing that probability exam or winning at the casino! Whether you are hitting the books or hitting the tables, working out probabilities can be a challenge. This book helps even the odds. The book covers set theory, counting, permutations and combinations, random variables, conditional probability, joint distributions, conditional expectations, gambling, and actuarial applications and probability modeling. And it is packed with real-life examples and straightforward, friendly explanations.

Fifty challenging probability problems. Remarkable selection of puzzlers, graded in difficulty, that illustrate both elementary and advanced aspects of probability. Selected for originality, general interest, or because they demonstrate valuable techniques, the problems are ideal as a supplement to courses in probability or statistics, or as stimulating recreation for the mathematically minded. Each problem is illustrated with a detailed solution. If you have a soft spot for problems in probability, this book is an inexpensive must.

Pages and pages of solved probability problems. Designed for students in various disciplines of engineering, science, mathematics, management, and business, this effective study tool includes hundreds of problems with step-by-step solutions and another 150 problems with hints or delayed answers. The solved problems illustrate and strongly reinforce vital theory and techniques. Topics taught include functions of random variables, expectation and limit theorems, estimation theory, decision theory, and queuing theory.

A fresh approach to probability. A pleasant surprise; a book that makes probability theory easy to understand. The author uses colorful examples (gambling, lotteries, etc.) and historical references (Newton, Einstein, etc.) to illustrate basic principles and stimulate reader interest. This book very clearly explains why probability works and how to apply it.

Probability theory and models. This is an introductory probability text for college students. It is, for example, the current textbook for 'Probabilistic Systems Analysis,' an introductory probability course at the Massachusetts Institute of Technology. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems). It also covers a number of more advanced topics - transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes.

A Bayesian approach to science. This introduction to probability was written by a scientist for scientists. The author shows how Bayesian theory can be applied to inference from incomplete information. The book is a pleasure to read, especially the author's entertaining arguments against conventional theory. That is not to say that it is an easy read; on the contrary, the math is high-level and the problems are challenging. To follow the author's presentation, the reader will need to be familiar with applied mathematics at an advanced undergraduate level.