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Probability and random number : a first guide to randomness

By: Sugita, Hiroshi.
Publisher: New Jersey : World Scientific, 2017Description: xi, 125 p. ; ill., 24 cm.ISBN: 9789813228252.Subject(s): Mathematics Applied | Binary numeral system | Chebyshev's inequality | Kolmogorov complexity | Law of large | Monte Carlo method | Partial recursive function | Primitive recursive function | Probability space | Pseudorandom | Stirling's formula | Bernoulli's theoremDDC classification: 519.2 Summary: This is a book of elementary probability theory that includes a chapter on algorithmic randomness. It rigorously presents definitions and theorems in computation theory, and explains the meanings of the theorems by comparing them with mechanisms of the computer, which is very effective in the current computer age. Random number topics have not been treated by any books on probability theory, only some books on computation theory. However, the notion of random number is necessary for understanding the essential relation between probability and randomness. The field of probability has changed very much, thus this book will make and leave a big impact even to expert probabilists. Readers from applied sciences will benefit from this book because it presents a very proper foundation of the Monte Carlo method with practical solutions, keeping the technical level no higher than 1st year university calculus.
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Books 519.2 SUG (Browse shelf) Available 034052

Includes bibliographical references and index.

This is a book of elementary probability theory that includes a chapter on algorithmic randomness. It rigorously presents definitions and theorems in computation theory, and explains the meanings of the theorems by comparing them with mechanisms of the computer, which is very effective in the current computer age. Random number topics have not been treated by any books on probability theory, only some books on computation theory. However, the notion of random number is necessary for understanding the essential relation between probability and randomness. The field of probability has changed very much, thus this book will make and leave a big impact even to expert probabilists. Readers from applied sciences will benefit from this book because it presents a very proper foundation of the Monte Carlo method with practical solutions, keeping the technical level no higher than 1st year university calculus.

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