Introduction to Probability

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Publisher : John Wiley & Sons
ISBN 13 : 1118548558
Total Pages : 548 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Introduction to Probability by : Narayanaswamy Balakrishnan

Download or read book Introduction to Probability written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2021-11-24 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRODUCTION TO PROBABILITY Discover practical models and real-world applications of multivariate models useful in engineering, business, and related disciplines In Introduction to Probability: Multivariate Models and Applications, a team of distinguished researchers delivers a comprehensive exploration of the concepts, methods, and results in multivariate distributions and models. Intended for use in a second course in probability, the material is largely self-contained, with some knowledge of basic probability theory and univariate distributions as the only prerequisite. This textbook is intended as the sequel to Introduction to Probability: Models and Applications. Each chapter begins with a brief historical account of some of the pioneers in probability who made significant contributions to the field. It goes on to describe and explain a critical concept or method in multivariate models and closes with two collections of exercises designed to test basic and advanced understanding of the theory. A wide range of topics are covered, including joint distributions for two or more random variables, independence of two or more variables, transformations of variables, covariance and correlation, a presentation of the most important multivariate distributions, generating functions and limit theorems. This important text: Includes classroom-tested problems and solutions to probability exercises Highlights real-world exercises designed to make clear the concepts presented Uses Mathematica software to illustrate the text’s computer exercises Features applications representing worldwide situations and processes Offers two types of self-assessment exercises at the end of each chapter, so that students may review the material in that chapter and monitor their progress Perfect for students majoring in statistics, engineering, business, psychology, operations research and mathematics taking a second course in probability, Introduction to Probability: Multivariate Models and Applications is also an indispensable resource for anyone who is required to use multivariate distributions to model the uncertainty associated with random phenomena.

Applied Probability Models with Optimization Applications

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Publisher : Courier Corporation
ISBN 13 : 0486318648
Total Pages : 224 pages
Book Rating : 4.4/5 (863 download)

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Book Synopsis Applied Probability Models with Optimization Applications by : Sheldon M. Ross

Download or read book Applied Probability Models with Optimization Applications written by Sheldon M. Ross and published by Courier Corporation. This book was released on 2013-04-15 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.

Probability Models and Applications

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Publisher : World Scientific Publishing Company
ISBN 13 : 9789813202030
Total Pages : 0 pages
Book Rating : 4.2/5 (2 download)

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Book Synopsis Probability Models and Applications by : Ingram Olkin

Download or read book Probability Models and Applications written by Ingram Olkin and published by World Scientific Publishing Company. This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Probability Models

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Publisher : Academic Press
ISBN 13 : 0123756871
Total Pages : 801 pages
Book Rating : 4.1/5 (237 download)

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Book Synopsis Introduction to Probability Models by : Sheldon M. Ross

Download or read book Introduction to Probability Models written by Sheldon M. Ross and published by Academic Press. This book was released on 2006-12-11 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Introduction to Probability Models

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Publisher : Elsevier
ISBN 13 : 0123736358
Total Pages : 801 pages
Book Rating : 4.1/5 (237 download)

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Book Synopsis Introduction to Probability Models by : Sheldon M. Ross

Download or read book Introduction to Probability Models written by Sheldon M. Ross and published by Elsevier. This book was released on 2007 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rosss classic bestseller has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries.

Interpreting Probability Models

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Publisher : SAGE
ISBN 13 : 9780803949997
Total Pages : 100 pages
Book Rating : 4.9/5 (499 download)

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Book Synopsis Interpreting Probability Models by : Tim Futing Liao

Download or read book Interpreting Probability Models written by Tim Futing Liao and published by SAGE. This book was released on 1994-06-30 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is the probability that something will occur, and how is that probability altered by a change in an independent variable? To answer these questions, Tim Futing Liao introduces a systematic way of interpreting commonly used probability models. Since much of what social scientists study is measured in noncontinuous ways and, therefore, cannot be analyzed using a classical regression model, it becomes necessary to model the likelihood that an event will occur. This book explores these models first by reviewing each probability model and then by presenting a systematic way for interpreting the results from each.

Probability Models

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Publisher : Springer Science & Business Media
ISBN 13 : 144715343X
Total Pages : 296 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Probability Models by : John Haigh

Download or read book Probability Models written by John Haigh and published by Springer Science & Business Media. This book was released on 2013-07-04 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to provide a sound introduction to the study of real-world phenomena that possess random variation. It describes how to set up and analyse models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability, such as that of a dice or cards, the idea of fairness in games of chance, and the random ways in which, say, birthdays are shared or particular events arise. Applications include branching processes, random walks, Markov chains, queues, renewal theory, and Brownian motion. This textbook contains many worked examples and several chapters have been updated and expanded for the second edition. Some mathematical knowledge is assumed. The reader should have the ability to work with unions, intersections and complements of sets; a good facility with calculus, including integration, sequences and series; and appreciation of the logical development of an argument. Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics.

Probability Models And Applications (Revised Second Edition)

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Publisher : World Scientific
ISBN 13 : 9813202068
Total Pages : 732 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Probability Models And Applications (Revised Second Edition) by : Ingram Olkin

Download or read book Probability Models And Applications (Revised Second Edition) written by Ingram Olkin and published by World Scientific. This book was released on 2019-09-03 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Probability

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Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 496 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Probability by : Gregory K. Miller

Download or read book Probability written by Gregory K. Miller and published by Wiley-Interscience. This book was released on 2006-08-25 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve Your Probability of Mastering This Topic This book takes an innovative approach to calculus-based probability theory, considering it within a framework for creating models of random phenomena. The author focuses on the synthesis of stochastic models concurrent with the development of distribution theory while also introducing the reader to basic statistical inference. In this way, the major stochastic processes are blended with coverage of probability laws, random variables, and distribution theory, equipping the reader to be a true problem solver and critical thinker. Deliberately conversational in tone, Probability is written for students in junior- or senior-level probability courses majoring in mathematics, statistics, computer science, or engineering. The book offers a lucid and mathematicallysound introduction to how probability is used to model random behavior in the natural world. The text contains the following chapters: Modeling Sets and Functions Probability Laws I: Building on the Axioms Probability Laws II: Results of Conditioning Random Variables and Stochastic Processes Discrete Random Variables and Applications in Stochastic Processes Continuous Random Variables and Applications in Stochastic Processes Covariance and Correlation Among Random Variables Included exercises cover a wealth of additional concepts, such as conditional independence, Simpson's paradox, acceptance sampling, geometric probability, simulation, exponential families of distributions, Jensen's inequality, and many non-standard probability distributions.

Probability Models for DNA Sequence Evolution

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Publisher : Springer Science & Business Media
ISBN 13 : 1475762852
Total Pages : 246 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Probability Models for DNA Sequence Evolution by : Rick Durrett

Download or read book Probability Models for DNA Sequence Evolution written by Rick Durrett and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: "What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences?" In approaching this question a number of probability models are introduced and anyalyzed.Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies that illustrate the use of these results.

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

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Publisher : Academic Press
ISBN 13 : 9780123814364
Total Pages : 170 pages
Book Rating : 4.8/5 (143 download)

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Book Synopsis Introduction to Probability Models, Student Solutions Manual (e-only) by : Sheldon M Ross

Download or read book Introduction to Probability Models, Student Solutions Manual (e-only) written by Sheldon M Ross and published by Academic Press. This book was released on 2010-01-01 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Probability Models, Student Solutions Manual (e-only)

Discrete Probability Models and Methods

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Publisher : Springer
ISBN 13 : 3319434764
Total Pages : 561 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Discrete Probability Models and Methods by : Pierre Brémaud

Download or read book Discrete Probability Models and Methods written by Pierre Brémaud and published by Springer. This book was released on 2017-01-31 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book.

Applied Probability Models

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Publisher : Brooks/Cole
ISBN 13 :
Total Pages : 360 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applied Probability Models by : Do Le Minh

Download or read book Applied Probability Models written by Do Le Minh and published by Brooks/Cole. This book was released on 2001 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended for a course in Probability Models at the undergraduate or graduate level, this book is designed for those who will actually use probability and is designed to fit diverse audiences (business students, applied engineering students, and biology students). The course focuses on applications of probability through the presentation of models rather than theory alone. In this practical and interesting book, author Do Le (Paul) Minh provides accessible coverage for a course in probability models. Minh motivates the material with interesting application problems relating to medicine, business, and engineering, many of which are based on real studies and applications. Throughout the book, he thoughtfully integrates the use of computers and spreadsheets to solve problems.

Probability Models

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Publisher : Springer Science & Business Media
ISBN 13 : 1447101693
Total Pages : 263 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Probability Models by : John Haigh

Download or read book Probability Models written by John Haigh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics. It describes how to set up and analyse models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability via dice and cards, the idea of fairness in games of chance, and the random ways in which, say, birthdays are shared or particular events arise. Applications include branching processes, random walks, Markov chains, queues, renewal theory, and Brownian motion. No specific knowledge of the subject is assumed, only a familiarity with the notions of calculus, and the summation of series. Where the full story would call for a deeper mathematical background, the difficulties are noted and appropriate references given. The main topics arise naturally, with definitions and theorems supported by fully worked examples and some 200 set exercises, all with solutions.

Models for Probability and Statistical Inference

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Publisher : John Wiley & Sons
ISBN 13 : 0470183403
Total Pages : 466 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Models for Probability and Statistical Inference by : James H. Stapleton

Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

Probability Models in Engineering and Science

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Publisher : CRC Press
ISBN 13 : 9780824723156
Total Pages : 770 pages
Book Rating : 4.7/5 (231 download)

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Book Synopsis Probability Models in Engineering and Science by : Haym Benaroya

Download or read book Probability Models in Engineering and Science written by Haym Benaroya and published by CRC Press. This book was released on 2005-06-24 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Probabilistic Models

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Publisher : Butterworth-Heinemann
ISBN 13 : 0128165464
Total Pages : 590 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Probabilistic Models by : Pijush Samui

Download or read book Handbook of Probabilistic Models written by Pijush Samui and published by Butterworth-Heinemann. This book was released on 2019-10-05 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. Explains the application of advanced probabilistic models encompassing multidisciplinary research Applies probabilistic modeling to emerging areas in engineering Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems