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Basic Probability (2nd Ed)

by Tijms Henk

A problem-centered introduction to probability

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Hardcover New English

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Awards & Recognition

  • Author recognition

    Author received the 2008 INFORMS Expository Writing Award

    The credited author is reported to have received the INFORMS Expository Writing Award in 2008.

AlbakiReads Editorial

A problem-centered introduction to probability

This second edition builds a foundation in probability for first-time learners, with coverage spanning Bayesian probability, computer simulation, the Poisson distribution, generating functions, bivariate normal density, and Markov chains. Its examples connect the subject with applications, including two court cases used in the new Bayesian material. Practice is a substantial part of the approach: the book includes problems, problem-solving strategies, answers to all problems, and worked solutions to selected ones. The range of topics makes it relevant across applied and quantitative fields while keeping the emphasis on core probability concepts.

Good fit for readers who enjoy

  • Students beginning probability in statistics or data science
  • Learners in mathematics, engineering, computer science, or business analytics seeking an introductory text
  • Readers who want a probability book with extensive problems and solutions

Themes

Foundations of probabilityBayesian probabilityProbability and computer simulationApplied probability and Markov chains

Based on publisher information and book metadata.

Book overview

The second edition represents an ongoing effort to make probability accessible to students in a wide range of fields such as mathematics, statistics and data science, engineering, computer science, and business analytics. The book is written for those learning about probability for the first time. Revised and updated, the book is aimed specifically at statistics and data science students who need a solid introduction to the basics of probability.

 

While retaining its focus on basic probability, including Bayesian probability and the interface between probability and computer simulation, this edition's significant revisions are as follows:

  • Many extra motivational examples and problems
  • New material on Bayesian probability, including two famous court cases
  • New sections on real-world applications of the Poisson distribution
  • New sections on generating functions and the bivariate normal density
  • New chapter on Markov chains, including Markov chain Monte Carlo simulation

 

The approach followed in the book is to develop probabilistic intuition before diving into details. The best way to learn probability is by practising on a lot of problems. Many instructive problems together with problem-solving strategies are given. Answers to all problems and worked-out solutions to selected problems are also provided.

 

Henk Tijms is the author of several textbooks in the area of applied probability. In 2008, he had received the prestigious INFORMS Expository Writing Award for his work. He is active in popularizing probability at Dutch high schools.

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