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Probability Models In Engineering And Science


Probability Models In Engineering And Science
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Probability Models In Engineering And Science


Probability Models In Engineering And Science
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Author : Haym Benaroya
language : en
Publisher: CRC Press
Release Date : 2005-06-24

Probability Models In Engineering And Science written by Haym Benaroya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-24 with Science categories.


Certainty exists only in idealized models. Viewed as the quantification of uncertainties, probabilitry and random processes play a significant role in modern engineering, particularly in areas such as structural dynamics. Unlike this book, however, few texts develop applied probability in the practical manner appropriate for engineers. Probability Models in Engineering and Science provides a comprehensive, self-contained introduction to applied probabilistic modeling. The first four chapters present basic concepts in probability and random variables, and while doing so, develop methods for static problems. The remaining chapters address dynamic problems, where time is a critical parameter in the randomness. Highlights of the presentation include numerous examples and illustrations and an engaging, human connection to the subject, achieved through short biographies of some of the key people in the field. End-of-chapter problems help solidify understanding and footnotes to the literature expand the discussions and introduce relevant journals and texts. This book builds the background today's engineers need to deal explicitly with the scatter observed in experimental data and with intricate dynamic behavior. Designed for undergraduate and graduate coursework as well as self-study, the text's coverage of theory, approximation methods, and numerical methods make it equally valuable to practitioners.



Introduction To Probability Models


Introduction To Probability Models
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Author : Sheldon M. Ross
language : en
Publisher: Academic Press
Release Date : 2006-12-11

Introduction To Probability Models written by Sheldon M. Ross and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-11 with Mathematics categories.


Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text. The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students. This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes. New to this Edition: - 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains - Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams - Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bank - Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field Hallmark features: - Superior writing style - Excellent exercises and examples covering the wide breadth of coverage of probability topics - Real-world applications in engineering, science, business and economics



Probability Models For Computer Science


Probability Models For Computer Science
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Author : Sheldon M. Ross
language : en
Publisher: Taylor & Francis US
Release Date : 2002

Probability Models For Computer Science written by Sheldon M. Ross and has been published by Taylor & Francis US this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.


The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners. Many interesting examples and exercises have been chosen to illuminate the techniques presented Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented



Introduction To Probability And Statistics For Engineers


Introduction To Probability And Statistics For Engineers
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Author : Milan Holický
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-08-04

Introduction To Probability And Statistics For Engineers written by Milan Holický and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-04 with Mathematics categories.


The theory of probability and mathematical statistics is becoming an indispensable discipline in many branches of science and engineering. This is caused by increasing significance of various uncertainties affecting performance of complex technological systems. Fundamental concepts and procedures used in analysis of these systems are often based on the theory of probability and mathematical statistics. The book sets out fundamental principles of the probability theory, supplemented by theoretical models of random variables, evaluation of experimental data, sampling theory, distribution updating and tests of statistical hypotheses. Basic concepts of Bayesian approach to probability and two-dimensional random variables, are also covered. Examples of reliability analysis and risk assessment of technological systems are used throughout the book to illustrate basic theoretical concepts and their applications. The primary audience for the book includes undergraduate and graduate students of science and engineering, scientific workers and engineers and specialists in the field of reliability analysis and risk assessment. Except basic knowledge of undergraduate mathematics no special prerequisite is required.



Introduction To Probability Models Student Solutions Manual E Only


Introduction To Probability Models Student Solutions Manual E Only
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Author : Sheldon M. Ross
language : en
Publisher: Academic Press
Release Date : 2010-01-01

Introduction To Probability Models Student Solutions Manual E Only written by Sheldon M. Ross and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-01 with Mathematics categories.


Introduction to Probability Models, Student Solutions Manual (e-only)



The Probability Companion For Engineering And Computer Science


The Probability Companion For Engineering And Computer Science
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Author : Adam Prügel-Bennett
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23

The Probability Companion For Engineering And Computer Science written by Adam Prügel-Bennett and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Business & Economics categories.


Using examples and building intuition, this friendly guide helps readers understand and use probabilistic tools from basic to sophisticated.



Probability With Applications In Engineering Science And Technology


Probability With Applications In Engineering Science And Technology
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Author : Matthew A. Carlton
language : en
Publisher: Springer
Release Date : 2017-03-30

Probability With Applications In Engineering Science And Technology written by Matthew A. Carlton and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-30 with Mathematics categories.


This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8—available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise). For a year-long course, core chapters (1-4) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a self-contained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations. New to this edition • Updated and re-worked Recommended Coverage for instructors, detailing which courses should use the textbook and how to utilize different sections for various objectives and time constraints • Extended and revised instructions and solutions to problem sets • Overhaul of Section 7.7 on continuous-time Markov chains • Supplementary materials include three sample syllabi and updated solutions manuals for both instructors and students



Probability And Statistics For Engineering And The Sciences


Probability And Statistics For Engineering And The Sciences
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Author : Jay Devore
language : en
Publisher: Cengage Learning
Release Date : 2007-01-26

Probability And Statistics For Engineering And The Sciences written by Jay Devore and has been published by Cengage Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-26 with Mathematics categories.


This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. This proven, accurate book and its excellent examples evidence Jay Devore’s reputation as an outstanding author and leader in the academic community. Devore emphasizes concepts, models, methodology, and applications as opposed to rigorous mathematical development and derivations. Through the use of lively and realistic examples, students go beyond simply learning about statistics-they actually put the methods to use. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.



Fundamentals Of Probability And Statistics For Engineers


Fundamentals Of Probability And Statistics For Engineers
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Author : T. T. Soong
language : en
Publisher: John Wiley and Sons
Release Date : 2004-03-26

Fundamentals Of Probability And Statistics For Engineers written by T. T. Soong and has been published by John Wiley and Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-26 with Mathematics categories.


This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.