000			03355nam a22005655i 4500
001			978-1-4471-5343-6
003			DE-He213
005			20140220082809.0
007			cr nn 008mamaa
008			130704s2013 xxk| s |||| 0|eng d
020			_a9781447153436 _9978-1-4471-5343-6
024	7		_a10.1007/978-1-4471-5343-6 _2doi
050		4	_aQA273.A1-274.9
050		4	_aQA274-274.9
072		7	_aPBT _2bicssc
072		7	_aPBWL _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.2 _223
100	1		_aHaigh, John. _eauthor.
245	1	0	_aProbability Models _h[electronic resource] / _cby John Haigh.
250			_a2nd ed. 2013.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2013.
300			_aXII, 287 p. 17 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Undergraduate Mathematics Series, _x1615-2085
505	0		_aProbability Spaces -- Conditional Probability and Independence -- Common Probability Distributions -- Random Variables -- Sums of Random Variables -- Convergence and Limit Theorems -- Stochastic Processes in Discrete Time -- Stochastic Processes in Continuous Time -- Appendix: Common Distributions and Mathematical Facts.
520			_aThe 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 popular second edition textbook contains many worked examples and several chapters have been updated and expanded. 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.
650		0	_aMathematics.
650		0	_aComputer science.
650		0	_aComputer simulation.
650		0	_aDistribution (Probability theory).
650		0	_aOperations research.
650	1	4	_aMathematics.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aSimulation and Modeling.
650	2	4	_aProbability and Statistics in Computer Science.
650	2	4	_aOperation Research/Decision Theory.
650	2	4	_aMathematical Applications in Computer Science.
650	2	4	_aMathematical Applications in the Physical Sciences.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781447153429
830		0	_aSpringer Undergraduate Mathematics Series, _x1615-2085
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4471-5343-6
912			_aZDB-2-SMA
999			_c94834 _d94834