The Pleasures of Probability

The purpose of this book is to introduce the basic notions of probability through the discussion of a variety of problems and applications. The most important feature is the attempt to explain fundamental ideas in classical probability to non-specialists whose only prerequisite is algebra. The book can be used as a text for a first course in probability. Each chapter ends with a few problems with answers at the end of the book.

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The purpose of "The Pleasures of Probability" is to introduce some of the most fundamental ideas in classical probability to a fairly general audience - reaching from mathematical amateurs to scientists, from students to professional mathematicians. The only prerequisites required are a decent background in elementary algebra and an interest in discussions of a variety of problems and applications in probability. The style is informal, and the chapters are more like essays on a particular topic than textbook treatments. Even well-known problems are often covered in more depth than usual in order to illustrate underlying ideas. The book can be used as a text for a first course in probability or as a companion to a text. Each chapter ends with a few problems, the answers to which are given at the end of the book.

Contenu
1: Cars, Goats, and Sample Spaces. 2: How to Count: Birthdays and Lotteries. 3: Conditional Probability: From Kings to Prisoners. 4: The Formula of Thomas Bayes and Other Matters. 5: The Idea of Independence, with Applications. 6: A Little Bit About Games. 7: Random Variables, Expectations, and More About Games. 8: Baseball Cards, The Law of Large Numbers, and Bad News for Gamblers. 9: From Traffic to Chocolate Chip Cookies with the Poisson Distribution. 10: The Desperate Case of the Gambler's Ruin. 11: Breaking Sticks, Tossing Needles, and More: Probability on Continuous Sample Spaces. 12: Normal Distribution, and Order from Diversity via the Central Limit Theorem. 13: Random Numbers: What They Are and How to Use Them. 14: Computers and Probability. 15: Statistics: Applying Probability to Make Decisions. 16: Roaming the Number Line with a Markov Chain: Dependence. 17: The Brownian Motion, and Other Processes in Continuous Time.