Probability Tales (Student Mathematical Library) by Charles M. Grinstead (PDF)

Description

This book explores four real-world topics through the lens of probability theory. It can be used to supplement a standard text in probability or statistics. Most elementary textbooks present the basic theory and then illustrate the ideas with some neatly packaged examples. Here the authors assume that the reader has seen, or is learning, the basic theory from another book and concentrate in some depth on the following topics: streaks, the stock market, lotteries, and fingerprints. This extended format allows the authors to present multiple approaches to problems and to pursue promising side discussions in ways that would not be possible in a book constrained to cover a fixed set of topics. To keep the main narrative accessible, the authors have placed the more technical mathematical details in appendices. The appendices can be understood by someone who has taken one or two semesters of calculus.

User’s Reviews

Editorial Reviews: Review … a wonderful description of four real-world problems from the discipline. … This book should be of interest to faculty teaching courses in probability or statistics looking for fresh insight and examples to enhance their courses. Highly recommended. –ChoiceThis nice little book by Grinstead, Peterson and Snell is devoted to four real world applications of probability theory. While the technical level is kept at a minimum, the authors focus on explaining how the real world problems can be translated into the language of probability and spend large parts of the text on motivating the models they use. This is done mostly by a large number of plots such that also readers with less mathematical background get a good feeling for the intuition behind the models . . . It was a great pleasure for me to read this book. In many parts, it reads almost like a novel but of course a very instructive one. At the same time, the text is a valuable source for any course on basic probability in giving a very detailed picture of how the theory can be used in real world applications. –H. M. Mai, Zentralblatt MATHThis book is the product of three authors who work together on Chance News, an online newsletter that reviews current issues in the news relating to probability and statistics. . . . Indeed, it turned out to be a gem. . . . This is a lively, conversational book, full of the good writing that characterized Chance News over the years. . . . One of the many strengths of the book is the authors’ ability to take a question and turn around and around to examine it from many sides without preconceived ideas. It’s a good model for students. –Bill Satzer, MAA Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐When I got this book the choice of topics were interesting. I was curious to see how those topics are modeled and how the mathematics is worked out to check the models. But none of that is done in this book. Instead the author’s propose the models, summarize their own findings on it by saying what they did, and leave it at that. The mathematics behind the probability and the statistical tests are not developed anywhere in this book. This is quite the surprise to me because this book is nothing like the other Student Mathematical Library books. I am only giving it one star for raising the interesting problems but beyond that I did not learn anything in this book, unfortunately.

⭐If you take a college course in Probability and find it less relevant to interesting aspects of the real world than you had hoped, then I strongly recommend this book as the way to rekindle your interest. It has three long chapters (on streaks in sports and elsewhere; the stock market; lotteries) and a shorter chapter on fingerprints. All are interesting and well written, and the first two in particular examine in substantial detail how the math and the data are related. Are streaks longer than one would expect “just by chance”? To what extent do stock returns follow a Normal or a power law distribution? I urge instructors of college courses to suggest this book as supplementary reading, and I do so myself.

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