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Probability Models and Applications (Revised Second Edition) by Ingram Olkin

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Last updated on Sep 06, 2024 07:05:17 EDTView all revisionsView all revisions

Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
Book Title
Probability Models and Applications (Revised Second Edition)
Publication Date
2019-09-09
Pages
732
ISBN
9789813202030
Publication Year
2017
Type
Textbook
Format
Hardcover
Language
English
Subject Area
Mathematics, Science
Publication Name
Probability Models and Applications
Author
Cyrus Derman, Leon J. Gleser, Ingram Olkin
Publisher
World Industries Scientific Publishing Co Pte LTD
Subject
Probability & Statistics / General, Applied, Research & Methodology
Item Weight
0 Oz
Number of Pages
734 Pages

About this product

Product Identifiers

Publisher
World Industries Scientific Publishing Co Pte LTD
ISBN-10
9813202033
ISBN-13
9789813202030
eBay Product ID (ePID)
234590389

Product Key Features

Number of Pages
734 Pages
Language
English
Publication Name
Probability Models and Applications
Subject
Probability & Statistics / General, Applied, Research & Methodology
Publication Year
2017
Type
Textbook
Author
Cyrus Derman, Leon J. Gleser, Ingram Olkin
Subject Area
Mathematics, Science
Format
Hardcover

Dimensions

Item Weight
0 Oz

Additional Product Features

Edition Number
2
Intended Audience
Trade
LCCN
2019-024424
Dewey Edition
19
Dewey Decimal
519.2
Synopsis
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.
LC Classification Number
QA273

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