Probability models and applications

By:

Olkin, Ingram

Contributor(s):

Material type: Text

TextPublication details: New Jersey World Scientific 2020Edition: 2ndDescription: xv,715pISBN:

9789813202047

Subject(s):

DDC classification:

519.2 23 OL-P

LOC classification:

QA273 .O4 2019

Summary: "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. Numerous examples with actual data where probability models can be applied in practice"--

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Holdings
Item type	Home library	Collection	Call number	Status	Date due	Barcode
Print	OPJGU Sonepat- Campus Main Library	General Books	519.2 OL-P (Browse shelf(Opens below))	Available		143370

Includes bibliographical references and indexes.

"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. Numerous examples with actual data where probability models can be applied in practice"--

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