Introduction to Probability with Texas Hold’em Examples

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Introduction to Probability with Texas Hold’em Examples illustrates both standard and advanced probability topics using the popular poker game of Texas Hold’em, rather than the typical balls in urns. The author uses students’ natural interest in poker to teach important concepts in probability.

This classroom-tested book covers the main subjects of a standard undergraduate probability course, including basic probability rules, standard models for describing collections of data, and the laws of large numbers. It also discusses several more advanced topics, such as the ballot theorem, the arcsine law, and random walks, as well as some specialized poker issues, such as the quantification of luck and skill in Texas Hold’em. Homework problems are provided at the end of each chapter.

The author includes examples of actual hands of Texas Hold’em from the World Series of Poker and other major tournaments and televised games. He also explains how to use R to simulate Texas Hold’em tournaments for student projects. R functions for running the tournaments are freely available from CRAN (in a package called holdem).

Table of Contents

Probability Basics

Meaning of Probability

Basic Terminology

Axioms of Probability

Venn Diagrams

General Addition Rule

Counting Problems

Sample Spaces with Equally Probable Events

Multiplicative Counting Rule

Permutations

Combinations

Conditional Probability and Independence

Conditional Probability

Independence

Multiplication Rules

Bayes’ Rule and Structured Hand Analysis

Expected Value and Variance

Cumulative Distribution Function and Probability Mass Function

Expected Value

Pot Odds

Luck and Skill in Texas Hold’em

Variance and Standard Deviation

Markov and Chebyshev Inequalities

Moment Generating Functions

Discrete Random Variables

Bernoulli Random Variables

Binomial Random Variables

Geometric Random Variables

Negative Binomial Random Variables

Poisson Random Variables

Continuous Random Variables

Probability Density Functions

Expected Value, Variance, and Standard Deviation

Uniform Random Variables

Exponential Random Variables

Normal Random Variables

Pareto Random Variables

Continuous Prior and Posterior Distributions

Collections of Random Variables

Expected Value and Variance of Sums of Random Variables

Conditional Expectation

Laws of Large Numbers and the Fundamental Theorem of Poker

Central Limit Theorem

Confidence Intervals for the Sample Mean

Random Walks

Simulation and Approximation Using Computers

Appendix A: Abbreviated Rules of Texas Hold’em

Appendix B: Glossary of Poker Terms

Appendix C: Solutions to Selected Odd-Numbered Exercises

References and Suggested Reading

Index

Exercises appear at the end of each chapter.

Reviews

it is the laserlike focus of the examples and exercises that sets this book apart from other probability textbooks at this level. … The book is incredibly well-researched — examples are drawn from actual televised poker games, and many explorations of the probabilities in play in a given game situation conclude with a sentence about what really happened, which is a nice touch.

—Mark Bollman, MAA Reviews, February 2012

Author/Editor Biography

Frederic Paik Schoenberg is a professor and graduate vice-chair of statistics at UCLA. He is also co-editor of the Journal of Environmental Statistics. He earned a Ph.D. in statistics from UC Berkeley. His research interests include point processes, image analysis, time series, and applications in seismology and fire ecology.

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