03361nam a22005777a 4500001001500000003000900015005001700024007001500041008004100056020001800097024003500115050001900150050001600169072001600185072001700201072002300218082001400241100002600255245006400281250001800345264005900363300004400422336002600466337002600492338003600518347002400554490005800578505032700636520110700963650001702070650002502087650002102112650002902133650002502162650003502187650002602222650002602248650001902274650001702293650004902310650002902359650005202388650004002440650005102480650005602531710003402587773002002621776003602641830005802677856004802735sulb-eb0021700BD-SySUS20160413122156.0cr nn 008mamaa130704s2013 xxk| s |||| 0|eng d a97814471534367 a10.1007/978-1-4471-5343-62doi 4aQA273.A1-274.9 4aQA274-274.9 7aPBT2bicssc 7aPBWL2bicssc 7aMAT0290002bisacsh04a519.22231 aHaigh, John.eauthor.10aProbability Modelsh[electronic resource] /cby John Haigh. a2nd ed. 2013. 1aLondon :bSpringer London :bImprint: Springer,c2013. aXII, 287 p. 17 illus.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aSpringer Undergraduate Mathematics Series,x1615-20850 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. 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. 0aMathematics. 0aOperations research. 0aDecision making. 0aMathematical statistics. 0aComputer simulation. 0aComputer sciencexMathematics. 0aComputer mathematics. 0aMathematical physics. 0aProbabilities.14aMathematics.24aProbability Theory and Stochastic Processes.24aSimulation and Modeling.24aProbability and Statistics in Computer Science.24aOperation Research/Decision Theory.24aMathematical Applications in Computer Science.24aMathematical Applications in the Physical Sciences.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9781447153429 0aSpringer Undergraduate Mathematics Series,x1615-208540uhttp://dx.doi.org/10.1007/978-1-4471-5343-6