Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses.
New to the Second Edition
Axiomatic introduction of probability
Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap
More exercises at the end of each chapter
Additional MATLAB(R) codes, particularly new commands of the Statistics Toolbox
In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET).
Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.
Автор: Michael Baron Название: Probability and Statistics for Computer Scientists, Third Edition ISBN: 1138044482 ISBN-13(EAN): 9781138044487 Издательство: Taylor&Francis Цена: 10626 р. Наличие на складе: Есть у поставщикаПоставка под заказ. Описание: Probability and statistical methods, simulation techniques, and modeling tools. This third edition textbook adds R, including codes for data analysis examples, helps students solve problems, make optimal decisions in select stochastic models, probabilities and forecasts, and evaluate performance of computer systems and networks.
In a technological society, virtually every engineer and scientist needs to be able to collect, analyze, interpret, and properly use vast arrays of data. This means acquiring a solid foundation in the methods of data analysis and synthesis. Understanding the theoretical aspects is important, but learning to properly apply the theory to real-world problems is essential.
Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition introduces the fundamentals of probability, statistics, reliability, and risk methods to engineers and scientists for the purposes of data and uncertainty analysis and modeling in support of decision making.
The third edition of this bestselling text presents probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. This provides a measure of continuity and shows the broad use of simulation as a computational tool to inform decision making processes. This edition also features expanded discussions of the analysis of variance, including single- and two-factor analyses, and a thorough treatment of Monte Carlo simulation. The authors not only clearly establish the limitations, advantages, and disadvantages of each method, but also show that data analysis is a continuum rather than the isolated application of different methods.
Like its predecessors, this book continues to serve its purpose well as both a textbook and a reference. Ultimately, readers will find the content of great value in problem solving and decision making, particularly in practical applications.
Автор: James L. Johnson Название: Probability and Statistics for Computer Science ISBN: 0471326720 ISBN-13(EAN): 9780471326724 Издательство: Wiley Рейтинг: Цена: 24486 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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 noteand Further Readings for reinforcement of content
Описание: This handbook brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians.
Автор: Durrett, Rick Название: Elementary probability for applications ISBN: 0521867568 ISBN-13(EAN): 9780521867566 Издательство: Cambridge Academ Рейтинг: Цена: 7246 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples. The examples contain all the old standards such as the birthday problem and Monty Hall, but also include a number of applications not found in other books, from areas as broad ranging as genetics, sports, finance, and inventory management.
Описание: Statistics have helped shape every area of science. Without the means to analyze critical data, none of the great disoveries of the past would be possible. This paperback reprint of a Wiley bestseller shows the development of these data analysis tools and the manner in which they aided technological development prior to 1750.
Автор: T. T. Soong Название: Fundamentals of Probability and Statistics for Engineers ISBN: 0470868147 ISBN-13(EAN): 9780470868140 Издательство: Wiley Рейтинг: Цена: 6468 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. This book includes more than 100 examples and 200 exercises, along with a solutions manual for instructors. It presents the fundamentals in probability and statistics along with their applications.
Автор: T. T. Soong Название: Fundamentals of Probability and Statistics for Engineers ISBN: 0470868139 ISBN-13(EAN): 9780470868133 Издательство: Wiley Рейтинг: Цена: 17527 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents the fundamentals in probability and statistics along with relevant applications. This book explains the concept of probabilistic modelling and the process of model selection, verification and analysis. It also demonstrates practical problem solving with examples and exercises.
Описание: Designed for the first course in probability and statistics taken by students majoring in engineering and the computing sciences, this text offers a presentation of applications and theory. It aims to develop the theoretical foundations for the statistical methods. It explores the practical implications of the formal results to problem-solving.
Автор: Spiegel Название: Schaum`s Outline of Probability And Statistics ISBN: 0071183574 ISBN-13(EAN): 9780071183574 Издательство: McGraw-Hill Цена: 1385 р. Наличие на складе: Поставка под заказ.
Описание: "Schaum's Outline of Probability and Statistics" has become a vital resource for the more than 977,000 college students who enroll in related probability and
statistics courses each year. Its big-picture, calculus-based approach makes it an especially authoritative reference for engineering and science majors. Now thoroughly updated, this
second edition includes vital new coverage of order statistics, best critical regions, likelihood ratio tests, and other key topics.Additional Information:Tertiary Education (US: College) BIC:PBT Probability & statistics
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses.
New to the Second Edition
Axiomatic introduction of probability
Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap
More exercises at the end of each chapter
Additional MATLAB(R) codes, particularly new commands of the Statistics Toolbox
In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET).
Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.
Автор: Johnson Название: Probability and Statistics for Computer Science ISBN: 0470383429 ISBN-13(EAN): 9780470383421 Издательство: Wiley Рейтинг: Цена: 12821 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Begins with basic definitions of probability distributions and random variables and then elaborates on their properties and applications. This book then treats the most common discrete and continuous distributions, shows their use in decision and estimation problems, and constructs computer algorithms for generating observations.
Описание: An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications This updated and revised edition of the popular classic 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.
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