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Probability : a lively introduction / Henk Tijms.

By: Material type: TextTextAnalytics: Show analyticsPublisher: Cambridge : Cambridge University Press, 2018Copyright date: ©2018Description: x, 535 pages : illustrations ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 1108418740
  • 9781108418744
  • 1108407846
  • 9781108407847
Subject(s): Genre/Form: Additional physical formats: ebook version :: No titleDDC classification:
  • 519.2 23
LOC classification:
  • QA273.2 .T55 2018
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 -- Appendix A. Counting methods -- Appendix B. Basics of set theory -- Appendix C. Some basic results from calculus -- Appendix D. Basics of Monte Carlo simulation.
Summary: "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 text - such as Bayesian inference, Markov chain Monte Carlo simulation, and Chernoff bounds."--Publisher's website.
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Includes bibliographical references and index.

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 -- Appendix A. Counting methods -- Appendix B. Basics of set theory -- Appendix C. Some basic results from calculus -- Appendix D. Basics of Monte Carlo simulation.

"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 text - such as Bayesian inference, Markov chain Monte Carlo simulation, and Chernoff bounds."--Publisher's website.

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