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Introduction to Probability Theory With Engineering Applications

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Release : 2021-08-05
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Kind : eBook
Book Rating : 257/5 ( reviews)

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Book Synopsis Introduction to Probability Theory With Engineering Applications by : Aly Farag

Download or read book Introduction to Probability Theory With Engineering Applications written by Aly Farag. This book was released on 2021-08-05. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Probability Theory with Engineering Applications provides students with a solid foundation in probability theory, which deals with the modeling of uncertainty, and illuminates several modern applications of probability in engineering, physics and data analysis. The text is organized into five chapters and three appendices. The opening chapter introduces the notion of probability as a model or representation for the uncertainty associated with statistical experiments. In additional chapters, students learn about random variables through explanations of discrete and continuous variables, conditional distribution, and statistical distribution. Students examine functions of one random variable, two random variables, and extensions to multivariable distributions. The final chapter covers random processes. Helpful appendices include six computer laboratories that correspond with the content in Chapters 2-5, assessment and review questions for each chapter, and basic results from linear algebra. The book is an ideal resource for courses in engineering, computer science, biomedicine, physics, and mathematics. It is also an excellent text for researchers seeking an overview in applied probability theory. It is assumed readers have a background in introductory calculus and computer programming.

Introduction to Probability

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Release : 2021-11-24
Genre : Mathematics
Kind : eBook
Book Rating : 558/5 ( reviews)

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Book Synopsis Introduction to Probability by : Narayanaswamy Balakrishnan

Download or read book Introduction to Probability written by Narayanaswamy Balakrishnan. This book was released on 2021-11-24. 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.

Introduction to Probability

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Release : 2017-11-02
Genre : Mathematics
Kind : eBook
Book Rating : 98X/5 ( reviews)

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Book Synopsis Introduction to Probability by : David F. Anderson

Download or read book Introduction to Probability written by David F. Anderson. This book was released on 2017-11-02. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Elementary Applications of Probability Theory

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Release : 2018-02-06
Genre : Mathematics
Kind : eBook
Book Rating : 959/5 ( reviews)

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Book Synopsis Elementary Applications of Probability Theory by : Henry C. Tuckwell

Download or read book Elementary Applications of Probability Theory written by Henry C. Tuckwell. This book was released on 2018-02-06. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences and engineering. The first chapter contains a summary of basic probability theory. Chapters two to five deal with random variables and their applications. Topics covered include geometric probability, estimation of animal and plant populations, reliability theory and computer simulation. Chapter six contains a lucid account of the convergence of sequences of random variables, with emphasis on the central limit theorem and the weak law of numbers. The next four chapters introduce random processes, including random walks and Markov chains illustrated by examples in population genetics and population growth. This edition also includes two chapters which introduce, in a manifestly readable fashion, the topic of stochastic differential equations and their applications.

Probability with Applications in Engineering, Science, and Technology

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Release : 2017-03-30
Genre : Mathematics
Kind : eBook
Book Rating : 011/5 ( reviews)

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Book Synopsis Probability with Applications in Engineering, Science, and Technology by : Matthew A. Carlton

Download or read book Probability with Applications in Engineering, Science, and Technology written by Matthew A. Carlton. This book was released on 2017-03-30. Available in PDF, EPUB and Kindle. Book excerpt: 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

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