Henk Tijms

Probability

A Lively Introduction

• Gebundenes Buch

Produktbeschreibung

Comprehensive, yet concise, this textbook is the go-to guide to learn why probability is so important and its applications.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 546
• Erscheinungstermin: 19. Oktober 2017
• Englisch
• Abmessung: 235mm x 157mm x 34mm
• Gewicht: 932g
• ISBN-13: 9781108418744
• ISBN-10: 1108418740
• Artikelnr.: 48579948

Autorenporträt

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.

Inhaltsangabe

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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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.

Rezensionen

'This is an attractive textbook for an introductory probability course at the upper undergraduate level. It covers not only the standard material for such a course (discrete probability, the axioms of probability, conditional probability, discrete and continuous random variables, jointly distributed random variables, limit theorems, Markov chains, etc.) but also some topics that might be considered more unusual, such as Kelly betting, renewal-reward stochastic processes, and the law of iterated logarithms. Topics from statistics (confidence intervals, Student-t distribution, Baysian inference, etc.) also appear. The book is quite well-written, nicely motivated, demonstrates considerable enthusiasm for the material, and gives lots of examples of the usefulness of probability. Mark Hunacek, MAA Reviews