本书简介:
The goal of this book is to introduce basic concepts of probability, statistics, decision theory, and game theory using games.Thematerial should be suitable for a college-level general education course for undergraduate college students who have taken an algebra or pre-algebra class. In our experience, motivated high-school students who have taken an algebra course should also be capable of handling the material.
The book is organized into 13 chapters, with about half focusing on general concepts that are illustrated using awide variety of games, and about half focusing specifically on well-known casino games. More specifically, the first two chapters of the book are dedicated to a basic discussion of utility and probability theory infinite, discrete spaces.Thenwemove to a discussionof fivepopular casino games: roulette, lotto, craps, blackjack, and poker. Roulette, which is one of the simplest casino games to play and analyze, is used to illustrate the basic concepts in probability such as expectations. Lotto is used tomotivate counting
rules and the notions of permutations and combinatorial numbers that allow us to compute probabilities in large equiprobable spaces.The games of craps and blackjack are used to illustrate and develop conditional probabilities. Finally, the discussion of poker is helpful to illustrate how many of the ideas from previous chapters fit in together.The last four chapters of the book are dedicated to game theory and strategic games. Since this book ismeant to support a general education course, we restrict attention to simultaneous and sequential games of perfect information and avoid games of imperfect information.
The book uses computer simulations to illustrate complex concepts and convince students that the calculations presented in the book are correct. Computer simulations have become a key tool in many areas of scientific inquiry, and we believe that it is important for students to experience how easy access to computing power has changed science over the last 25 years. During the development of the book, we experimented with using spreadsheets but decided that they did not provide enough flexibility. In the end we settled for using R (https://www.r-project.org). R is an interactive environment that allows users to easily implement simple simulations even if they have limited experience with programming. To facilitate its use, we have included an overview and introduction to the R in Appendix A, as well as sidebars in each chapter that introduces features of the language that are relevant for the examples discussed in them. With a little extra work, this book could be used as the basis for a course that introduces students to both probability/statistics and programming. Alternatively, the book can also be read while ignoring the R commands and focusing only on the graphs and other output generated by it.