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Titlebook: Probability Models; John Haigh Textbook 2013Latest edition Springer-Verlag London 2013 Distributions.Markov Processes.Probability.Random V

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发表于 2025-3-21 16:50:47 | 显示全部楼层 |阅读模式
书目名称Probability Models
编辑John Haigh
视频video
概述Very suitable for self-study.Provides many worked examples and exercises.Suitable for beginners; no prior knowledge of probability is needed.Includes supplementary material:
丛书名称Springer Undergraduate Mathematics Series
图书封面Titlebook: Probability Models;  John Haigh Textbook 2013Latest edition Springer-Verlag London 2013 Distributions.Markov Processes.Probability.Random V
描述.The purpose of this book is to provide a sound introduction to the study of real-world phenomena that possess random variation. It describes how to set up and analyse models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability, such as that of a dice or cards, the idea of fairness in games of chance, and the random ways in which, say, birthdays are shared or particular events arise..Applications include branching processes, random walks, Markov chains, queues, renewal theory, and Brownian motion. This textbook contains many worked examples and several chapters have been updated and expanded for the second edition. .Some mathematical knowledge is assumed. The reader should have the ability to work with unions, intersections and complements of sets; a good facility with calculus, including integration, sequences and series; and appreciation of the logical development of an argument. .Probability Models.is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics..
出版日期Textbook 2013Latest edition
关键词Distributions; Markov Processes; Probability; Random Variables; Stochastic Processes
版次2
doihttps://doi.org/10.1007/978-1-4471-5343-6
isbn_softcover978-1-4471-5342-9
isbn_ebook978-1-4471-5343-6Series ISSN 1615-2085 Series E-ISSN 2197-4144
issn_series 1615-2085
copyrightSpringer-Verlag London 2013
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John Haighpaths.Details important applications to a range of phenomenaPercolation theory describes the effects of the connectivity of microscopic or small-scale elements of a complex medium to its macroscopic or large-scale properties. It also describes the conditions under which there may be a continuously c
发表于 2025-3-22 07:21:24 | 显示全部楼层
John Haighale properties. It also describes the conditions under which there may be a continuously connected path of local elements across the medium. The point at which the path is formed is called the percolation threshold. Percolation theory also predicts that many macroscopic properties of complex media f
发表于 2025-3-22 09:27:56 | 显示全部楼层
John Haighpaths.Details important applications to a range of phenomenaPercolation theory describes the effects of the connectivity of microscopic or small-scale elements of a complex medium to its macroscopic or large-scale properties. It also describes the conditions under which there may be a continuously c
发表于 2025-3-22 15:35:38 | 显示全部楼层
发表于 2025-3-22 17:02:35 | 显示全部楼层
John Haighpaths.Details important applications to a range of phenomenaPercolation theory describes the effects of the connectivity of microscopic or small-scale elements of a complex medium to its macroscopic or large-scale properties. It also describes the conditions under which there may be a continuously c
发表于 2025-3-23 01:09:19 | 显示全部楼层
John Haighpaths.Details important applications to a range of phenomenaPercolation theory describes the effects of the connectivity of microscopic or small-scale elements of a complex medium to its macroscopic or large-scale properties. It also describes the conditions under which there may be a continuously c
发表于 2025-3-23 04:26:16 | 显示全部楼层
John Haighale properties. It also describes the conditions under which there may be a continuously connected path of local elements across the medium. The point at which the path is formed is called the percolation threshold. Percolation theory also predicts that many macroscopic properties of complex media f
发表于 2025-3-23 08:52:54 | 显示全部楼层
Probability Spaces, throw an ordinary die, then .={1,2,3,4,5,6}. Or you might switch on the television set and ascertain what proportion of the current programme remains to be broadcast. Here . would be the continuum of real numbers from zero to unity.
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