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Author : Adam Prügel-Bennett
Publisher : Cambridge University Press
Page : 475 pages
File Size : 49,9 Mb
Release : 2020-01-23
Category : Business & Economics
ISBN : 9781108480536
Using examples and building intuition, this friendly guide helps readers understand and use probabilistic tools from basic to sophisticated.
Author : Kishor S. Trivedi
Publisher : John Wiley & Sons
Page : 880 pages
File Size : 45,9 Mb
Release : 2016-06-30
Category : Computers
ISBN : 9781119314202
An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications Second edition now also available in Paperback. This updated and revised edition of the popular classic first edition relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance. This edition features an entirely new section on stochastic Petri nets—as well as new sections on system availability modeling, wireless system modeling, numerical solution techniques for Markov chains, and software reliability modeling, among other subjects. Extensive revisions take new developments in solution techniques and applications into account and bring this work totally up to date. It includes more than 200 worked examples and self-study exercises for each section. Probability and Statistics with Reliability, Queuing and Computer Science Applications, Second Edition offers a comprehensive introduction to probability, stochastic processes, and statistics for students of computer science, electrical and computer engineering, and applied mathematics. Its wealth of practical examples and up-to-date information makes it an excellent resource for practitioners as well. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Author : Jean Walrand
Publisher : Springer Nature
Page : 391 pages
File Size : 50,9 Mb
Release : 2021-06-22
Category : Computers
ISBN : 9783030499952
This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at [email protected]. This is an open access book.
Author : Jane M. Horgan
Publisher : John Wiley & Sons
Page : 496 pages
File Size : 42,9 Mb
Release : 2019-12-04
Category : Mathematics
ISBN : 9781119536925
Provides a comprehensive introduction to probability with an emphasis on computing-related applications This self-contained new and extended edition outlines a first course in probability applied to computer-related disciplines. As in the first edition, experimentation and simulation are favoured over mathematical proofs. The freely down-loadable statistical programming language R is used throughout the text, not only as a tool for calculation and data analysis, but also to illustrate concepts of probability and to simulate distributions. The examples in Probability with R: An Introduction with Computer Science Applications, Second Edition cover a wide range of computer science applications, including: testing program performance; measuring response time and CPU time; estimating the reliability of components and systems; evaluating algorithms and queuing systems. Chapters cover: The R language; summarizing statistical data; graphical displays; the fundamentals of probability; reliability; discrete and continuous distributions; and more. This second edition includes: improved R code throughout the text, as well as new procedures, packages and interfaces; updated and additional examples, exercises and projects covering recent developments of computing; an introduction to bivariate discrete distributions together with the R functions used to handle large matrices of conditional probabilities, which are often needed in machine translation; an introduction to linear regression with particular emphasis on its application to machine learning using testing and training data; a new section on spam filtering using Bayes theorem to develop the filters; an extended range of Poisson applications such as network failures, website hits, virus attacks and accessing the cloud; use of new allocation functions in R to deal with hash table collision, server overload and the general allocation problem. The book is supplemented with a Wiley Book Companion Site featuring data and solutions to exercises within the book. Primarily addressed to students of computer science and related areas, Probability with R: An Introduction with Computer Science Applications, Second Edition is also an excellent text for students of engineering and the general sciences. Computing professionals who need to understand the relevance of probability in their areas of practice will find it useful.
Author : Michael Baron
Publisher : CRC Press
Page : 427 pages
File Size : 40,7 Mb
Release : 2018-11-14
Category : Mathematics
ISBN : 9781420011425
In modern computer science, software engineering, and other fields, the need arises to make decisions under uncertainty. Presenting probability and statistical methods, simulation techniques, and modeling tools, Probability and Statistics for Computer Scientists helps students solve problems and make optimal decisions in uncertain conditions
Author : J. Susan Milton
Publisher : McGraw-Hill Europe
Page : 450 pages
File Size : 40,5 Mb
Release : 2012-11
Category : Electronic data processing
ISBN : 0071087850
Helps students to understand statistical methods and reasoning as well as practice in using them. This book includes examples and exercises that are specially chosen for those looking for careers in the engineering and computing sciences. It is intended as a first course in probability and applied statistics for students.
Author : Janet Susan Milton,Jesse C. Arnold
Publisher : Unknown
Page : 643 pages
File Size : 43,9 Mb
Release : 1986
Category : Electronic data processing
ISBN : 0071005749
Author : Arnold O. Allen
Publisher : Academic Press
Page : 408 pages
File Size : 50,9 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483266596
Probability, Statistics, and Queueing Theory: With Computer Science Applications focuses on the use of statistics and queueing theory for the design and analysis of data communication systems, emphasizing how the theorems and theory can be used to solve practical computer science problems. This book is divided into three parts. The first part discusses the basic concept of probability, probability distributions commonly used in applied probability, and important concept of a stochastic process. Part II covers the discipline of queueing theory, while Part III deals with statistical inference. This publication is designed as a junior-senior level textbook on applied probability and statistics with computer science applications, but is also a self-study book for practicing computer science (data processing) professionals.
Author : Sheldon M. Ross
Publisher : Taylor & Francis US
Page : 304 pages
File Size : 40,8 Mb
Release : 2002
Category : Computers
ISBN : 0125980515
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
Author : Charles Therrien,Murali Tummala
Publisher : CRC Press
Page : 431 pages
File Size : 54,8 Mb
Release : 2018-09-03
Category : Computers
ISBN : 9781439897492
With updates and enhancements to the incredibly successful first edition, Probability and Random Processes for Electrical and Computer Engineers, Second Edition retains the best aspects of the original but offers an even more potent introduction to probability and random variables and processes. Written in a clear, concise style that illustrates the subject’s relevance to a wide range of areas in engineering and physical and computer sciences, this text is organized into two parts. The first focuses on the probability model, random variables and transformations, and inequalities and limit theorems. The second deals with several types of random processes and queuing theory. New or Updated for the Second Edition: A short new chapter on random vectors that adds some advanced new material and supports topics associated with discrete random processes Reorganized chapters that further clarify topics such as random processes (including Markov and Poisson) and analysis in the time and frequency domain A large collection of new MATLAB®-based problems and computer projects/assignments Each Chapter Contains at Least Two Computer Assignments Maintaining the simplified, intuitive style that proved effective the first time, this edition integrates corrections and improvements based on feedback from students and teachers. Focused on strengthening the reader’s grasp of underlying mathematical concepts, the book combines an abundance of practical applications, examples, and other tools to simplify unnecessarily difficult solutions to varying engineering problems in communications, signal processing, networks, and associated fields.
Author : Matthew A. Carlton,Jay L. Devore
Publisher : Springer
Page : 610 pages
File Size : 49,5 Mb
Release : 2017-03-30
Category : Mathematics
ISBN : 9783319524016
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
Author : Janet Susan Milton,Jesse C. Arnold
Publisher : McGraw-Hill Science, Engineering & Mathematics
Page : 0 pages
File Size : 41,5 Mb
Release : 1995
Category : Computer science
ISBN : 0070426236
This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.
Author : Janet Susan Milton,Jesse C. Arnold
Publisher : Unknown
Page : 798 pages
File Size : 46,8 Mb
Release : 2002-11-01
Category : Computer science
ISBN : 0071242481
This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.
Author : Sheldon M. Ross
Publisher : Elsevier
Page : 640 pages
File Size : 46,6 Mb
Release : 2004-07-21
Category : Mathematics
ISBN : 0080470319
Introduction to Probability and Statistics for Engineers and Scientists, Third Edition, provides an introduction to applied probability and statistics for engineering or science majors . This updated text emphasizes the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. The Third Edition includes new exercises, examples, homework problems, updated statistical material, and more. New exercises and data examples include: the one-sided Chebyshev inequality for data; logistics distribution and logistic regression; estimation and testing in proofreader problems; and product form estimates of life distributions. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and the enclosed CD-ROM includes unique, easy-to-use software that automates the required computations. This book is intended primarily for undergraduates in engineering and the sciences, and would be of particular interest to students in Industrial Engineering, Operations Research, Statistics, Mathematics, Computer Science, Electrical Engineering, Civil Engineering, Chemical Engineering, and Quantitative Business. It could also be of value in a graduate introductory course in probability and statistics. New in this edition: * New exercises and data examples including: - The One-sided Chebyshev Inequality for Data - The Logistics Distribution and Logistic Regression - Estimation and Testing in proofreader problems - Product Form Estimates of Life Distributions - Observational Studies * Updated statistical material * New, contemporary applications Hallmark features: * Reflects Sheldon Ross's masterfully clear exposition * Contains numerous examples, exercises, and homework problems * Unique, easy-to-use software automates required computations * Applies probability theory to everyday statistical problems and situations * Careful development of probability, modeling, and statistical procedures leads to intuitive understanding * Instructor's Solutions Manual is available to adopters
Author : James L. Johnson
Publisher : John Wiley & Sons
Page : 764 pages
File Size : 53,6 Mb
Release : 2011-09-09
Category : Mathematics
ISBN : 9781118165966
Comprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: "to present the mathematical analysis underlying probability results" Special emphases on simulation and discrete decision theory Mathematically-rich, but self-contained text, at a gentle pace Review of calculus and linear algebra in an appendix Mathematical interludes (in each chapter) which examine mathematical techniques in the context of probabilistic or statistical importance Numerous section exercises, summaries, historical notes, and Further Readings for reinforcement of content
