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010   $a3-030-32323-4
024 7 $a10.1007/978-3-030-32323-3
035   $a(CKB)4100000009758976
035   $a(DE-He213)978-3-030-32323-3
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035   $a(PPN)258064846
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100   $a20191105d2019      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aBasics of Probability and Stochastic Processes /$fby Esra Bas
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (IX, 307 p.) 
311   $a3-030-32322-6 
327   $aCombinatorial Analysis -- Basic Concepts in Probability -- Conditional Probability, Bayes?s Formula, Independent Events -- Introduction to Random Variables -- Discrete Random Variables -- Continuous Random Variables -- Other Selected Topics in Basic Probability -- A Brief Introduction to Stochastic Processes -- A Brief Introduction to Point Process, Counting Process, Renewal Process, Regenerative Process, Poisson Process -- Poisson Process -- Renewal Process -- An Introduction to Markov Chains -- Special Discrete-Time Markov Chains -- Continuous-Time Markov Chains -- An Introduction to Queueing Models -- Introduction to Brownian Motion -- Basics of Martingales -- Basics of Reliability Theory.
330   $aThis textbook explores probability and stochastic processes at a level that does not require any prior knowledge except basic calculus. It presents the fundamental concepts in a step-by-step manner, and offers remarks and warnings for deeper insights. The chapters include basic examples, which are revisited as the new concepts are introduced. To aid learning, figures and diagrams are used to help readers grasp the concepts, and the solutions to the exercises and problems. Further, a table format is also used where relevant for better comparison of the ideas and formulae. The first part of the book introduces readers to the essentials of probability, including combinatorial analysis, conditional probability, and discrete and continuous random variable. The second part then covers fundamental stochastic processes, including point, counting, renewal and regenerative processes, the Poisson process, Markov chains, queuing models and reliability theory. Primarily intended for undergraduate engineering students, it is also useful for graduate-level students wanting to refresh their knowledge of the basics of probability and stochastic processes.
606   $aMarkov processes
606   $aEngineering mathematics
606   $aCombinatorics
606   $aQuality control
606   $aReliability
606   $aIndustrial safety
606   $aMarkov model$3https://scigraph.springernature.com/ontologies/product-market-codes/M27010
606   $aEngineering Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/T11030
606   $aCombinatorics$3https://scigraph.springernature.com/ontologies/product-market-codes/M29010
606   $aQuality Control, Reliability, Safety and Risk$3https://scigraph.springernature.com/ontologies/product-market-codes/T22032
615  0$aMarkov processes.
615  0$aEngineering mathematics.
615  0$aCombinatorics.
615  0$aQuality control.
615  0$aReliability.
615  0$aIndustrial safety.
615 14$aMarkov model.
615 24$aEngineering Mathematics.
615 24$aCombinatorics.
615 24$aQuality Control, Reliability, Safety and Risk.
676   $a519.2
700   $aBas$b Esra$4aut$4http://id.loc.gov/vocabulary/relators/aut$0781000
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910360854903321
996   $aBasics of Probability and Stochastic Processes$91668169
997   $aUNINA