dc.contributor.author Kachapova, F dc.date.accessioned 2013-06-07T07:23:43Z dc.date.available 2013-06-07T07:23:43Z dc.date.copyright 2013 dc.date.issued 2013-06-07 dc.identifier.citation Journal of Mathematics and Statistics, vol.9(3), pp.149 - 154 dc.identifier.issn 1549-3644 dc.identifier.uri http://hdl.handle.net/10292/5423 dc.description.abstract Stochastic processes have many useful applications and are taught in several university programmes. Students often encounter difficulties in learning stochastic processes and Markov chains, in particular. In this article we describe a teaching strategy that uses transition diagrams to represent a Markov chain and to re-define properties of its states in simple terms of directed graphs. This strategy utilises the students’ intuition and makes the learning of complex concepts about Markov chains faster and easier. The method is illustrated by worked examples. The described strategy helps students to master properties of finite Markov chains, so they have a solid basis for the study of infinite Markov chains and other stochastic processes. dc.publisher Science Publications dc.relation.uri http://dx.doi.org/10.3844/jmssp.2013.149.154 dc.rights Science Publications publishes a collection of peer-reviewed, open access scientific journals covering all areas of science, technology and medicine. All articles published with Science Publications publishes follow the open access policy which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. dc.subject Transition diagram dc.subject Transition matrix dc.subject Markov chain dc.subject First passage time dc.subject Persistent state dc.subject Transient state dc.subject Periodic state dc.subject Inter-communicating states dc.title Representing Markov chains with transition diagrams dc.type Journal Article dc.rights.accessrights OpenAccess dc.identifier.doi 10.3844/jmssp.2013.149.154 aut.relation.endpage 154 aut.relation.issue 3 aut.relation.startpage 149 aut.relation.volume 9 pubs.elements-id 143371
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