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Probability Models And Applications (Revised Second Edition) - Ingram (Stanford Univ Olkin - Bog

Bag om Probability Models And Applications (Revised Second Edition)

Written by renowned experts in the field, this reissue of a textbook has as its unifying theme the role that probability models have had, and continue to have, in scientific and practical applications. It includes many examples, with actual data, of real-world use of probability models, while expositing the mathematical theory of probability at an introductory calculus-based level. Detailed descriptions of the properties and applications of probability models that have successfully modeled real phenomena are given, as well as an explanation of methods for testing goodness of fit of these models. Readers will receive a firm foundation in techniques for deriving distributions of various summaries of data that will prepare them for subsequent studies of statistics, as well as a solid grounding in concepts such as that of conditional probability that will prepare them for more advanced courses in stochastic processes.

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  • Sprog:
  • Ukendt
  • ISBN:
  • 9789813202030
  • Indbinding:
  • Hardback
  • Sideantal:
  • 732
  • Udgivet:
  • 9. September 2019
  • Udgave:
  • 2
  • Størrelse:
  • 186x258x45 mm.
  • Vægt:
  • 1544 g.
  • 2-3 uger.
  • 19. Juli 2024
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Beskrivelse af Probability Models And Applications (Revised Second Edition)

Written by renowned experts in the field, this reissue of a textbook has as its unifying theme the role that probability models have had, and continue to have, in scientific and practical applications. It includes many examples, with actual data, of real-world use of probability models, while expositing the mathematical theory of probability at an introductory calculus-based level. Detailed descriptions of the properties and applications of probability models that have successfully modeled real phenomena are given, as well as an explanation of methods for testing goodness of fit of these models. Readers will receive a firm foundation in techniques for deriving distributions of various summaries of data that will prepare them for subsequent studies of statistics, as well as a solid grounding in concepts such as that of conditional probability that will prepare them for more advanced courses in stochastic processes.

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