Probability: A Lively Introduction

Probability: A Lively Introduction

by Henk Tijms
ISBN-10:
1108407846
ISBN-13:
9781108407847
Pub. Date:
10/06/2017
Publisher:
Cambridge University Press
ISBN-10:
1108407846
ISBN-13:
9781108407847
Pub. Date:
10/06/2017
Publisher:
Cambridge University Press
Probability: A Lively Introduction

Probability: A Lively Introduction

by Henk Tijms
$39.99
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Overview

Probability has applications in many areas of modern science, not to mention in our daily life. Its importance as a mathematical discipline cannot be overrated, and it is a fascinating and surprising topic in its own right. This engaging textbook with its easy-to-follow writing style provides a comprehensive yet concise introduction to the subject. It covers all of the standard material for undergraduate and first-year-graduate-level courses as well as many topics that are usually not found in standard texts, such as Bayesian inference, Markov chain Monte Carlo simulation, and Chernoff bounds.

Product Details

ISBN-13: 9781108407847
Publisher: Cambridge University Press
Publication date: 10/06/2017
Edition description: New Edition
Pages: 546
Product dimensions: 5.98(w) x 8.98(h) x 0.94(d)

About the Author

Henk Tijms is emeritus professor at the Vrije University, Amsterdam. He is the author of several textbooks and numerous papers on applied probability and stochastic optimization. In 2008, Henk Tijms received the prestigious INFORMS Expository Writing Award for his publications and books. His activities also include the popularization of probability to high school students and the general public; he also regularly contributed to the Numberplay blog of the New York Times with probability puzzles.

Table of Contents

1. Foundations of probability theory; 2. Conditional probability; 3. Discrete random variables; 4. Continuous random variables; 5. Jointly distributed random variables; 6. Multivariate normal distribution; 7. Conditioning by random variables; 8. Generating functions; 9. Additional topics in probability; 10. Discrete-time Markov chains; 11. Continuous-time Markov chains.
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