Introduction to Probability Models.

By:

Ross, Sheldon M [author.]

Material type: Text

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780443187612
0443187614

Subject(s):

DDC classification:

519.2 ROS 2024 23/eng/20230724

LOC classification:

QA273 .R84 2024

Summary: Introduction to Probability Models: Thirteenth Edition is available in two volumes: an Elementary edition appropriate for undergraduate use and an Advanced edition for graduate use. Together, and through their hallmark exercises and real examples, both versions offer a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Users will find comprehensive information that introduces them to the foundations of probability modeling and stochastic processes from Random Variables, to Markov Chains and Renewal Theory.

List(s) this item appears in: New Book 2024

Average rating: 0.0 (0 votes)

Holdings ( 1 )
Title notes ( 3 )

Holdings
Item type	Current library	Home library	Collection	Shelving location	Call number	Status	Date due	Barcode	Item holds
Open Collection	FIRST CITY UNIVERSITY COLLEGE	FIRST CITY UNIVERSITY COLLEGE	Open Collection	FCUC Library	519.2 ROS 2024 (Browse shelf(Opens below))	Available		00025112

Total holds: 0

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Previous	519.2 HAS 1997 Probability and statistics /	519.2 ROS 1988 A first course in probability /	519.2 ROS 1991 A Course In Simulation	519.2 ROS 2024 Introduction to Probability Models.	519.202462 VIN 1998 Probability And Random Process For Electrical Engineers	519.4 ATK 1989 Numerical methods with Fortran 77 :	519.4 ATK 2004 Elementary numerical analysis /	Next

Previous edition: 2019.

Includes bibliographical references and index.

Introduction to Probability Models: Thirteenth Edition is available in two volumes: an Elementary edition appropriate for undergraduate use and an Advanced edition for graduate use. Together, and through their hallmark exercises and real examples, both versions offer a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Users will find comprehensive information that introduces them to the foundations of probability modeling and stochastic processes from Random Variables, to Markov Chains and Renewal Theory.