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Probability : a lively introduction / Henk Tijms, Vrije Universiteit, Amsterdam.

By: Contributor(s): Material type: TextTextPublication details: united kingdom Cambridge University Press 2018Edition: 1stDescription: x, 535 pg. : 23 cmISBN:
  • 9781108418744 (hardback : alk. paper)
  • 9781108407847 (pbk. : alk. paper)
Subject(s): DDC 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.
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
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Holdings
Item type Current library Call number Status Date due Barcode
Books Books KMTC:LAKE VICTORIA CAMPUS General Stacks QA273.2 .T55 2018 (Browse shelf(Opens below)) Available LVC/844

Includes 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.

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

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