Описание: Presents elementary probability theory with applications that illustrate the theory. This book reviews the basic elements of differential calculus which are used in the material to follow. It is suitable for students in pure and applied sciences such as mathematics, engineering, computer science, finance and economics.
Описание: A complete guide to the theory and practical applications of probability theory An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory.
Автор: Schinazi Название: Probability with Statistical Applications ISBN: 081768249X ISBN-13(EAN): 9780817682491 Издательство: Springer Цена: 6791 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Probability With Statistical Applications offers a practical introduction to probability for undergraduates at all levels with different backgrounds and views towards applications. Calculus is a prerequisite for understanding the basic concepts, however the book is written with a sensitivity to students’ common difficulties with calculus that does not obscure the thorough treatment of the probability content. The first six chapters of this text neatly and concisely cover the material traditionally required by most undergraduate programs for a first course in probability.The comprehensive text includes a multitude of new examples and exercises, and careful revisions throughout. Particular attention is given to the expansion of the last three chapters of the book with the addition of two entirely new chapters on “Finding and Comparing Estimators” and “Multiple Linear Regression.” The classroom-tested material presented in this second edition textbook forms the basis for a second course introducing mathematical statistics.
Based on the author's course at NYU, Linear Algebra and Probability for Computer Science Applicationsgives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the chapters discuss relevant MATLAB(R) functions and features and give sample assignments in MATLAB; the author's website provides the MATLAB code from the book.
After an introductory chapter on MATLAB, the text is divided into two sections. The section on linear algebra gives an introduction to the theory of vectors, matrices, and linear transformations over the reals. It includes an extensive discussion on Gaussian elimination, geometric applications, and change of basis. It also introduces the issues of numerical stability and round-off error, the discrete Fourier transform, and singular value decomposition. The section on probability presents an introduction to the basic theory of probability and numerical random variables; later chapters discuss Markov models, Monte Carlo methods, information theory, and basic statistical techniques. The focus throughout is on topics and examples that are particularly relevant to computer science applications; for example, there is an extensive discussion on the use of hidden Markov models for tagging text and a discussion of the Zipf (inverse power law) distribution.
Examples and Programming Assignments The examples and programming assignments focus on computer science applications. The applications covered are drawn from a range of computer science areas, including computer graphics, computer vision, robotics, natural language processing, web search, machine learning, statistical analysis, game playing, graph theory, scientific computing, decision theory, coding, cryptography, network analysis, data compression, and signal processing.
Homework Problems Comprehensive problem sections include traditional calculation exercises, thought problems such as proofs, and programming assignments that involve creating MATLAB functions.
Автор: M. M. Rao Название: Probability Theory with Applications, ISBN: 0125804806 ISBN-13(EAN): 9780125804806 Издательство: Elsevier Science Рейтинг: Цена: 5429 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This introductory text helps readers with no prior exposure to probability and statistics become proficient in various statistical techniques. Focusing on both descriptive and inferential statistics, the book begins with descriptive statistics before introducing the fundamentals of probability theory underlying many of the techniques.
Описание: Probability comes of age with this, the first dictionary of probability and its applications in English, which supplies a guide to the concepts and vocabulary of this rapidly expanding field. Besides the basic theory of probability and random processes, applications covered here include financial and insurance mathematics, operations research (including queueing, reliability, and inventories), decision and game theory, optimization, time series, networks, and communication theory, as well as classic problems and paradoxes. The dictionary is reliable, stable, concise, and cohesive. Each entry provides a rigorous definition, a sketch of the context, and a reference pointing the reader to the wider literature. Judicious use of figures makes complex concepts easier to follow without oversimplifying. As the only dictionary on the market, this will be a guiding reference for all those working in, or learning, probability together with its applications.
Описание: Now inits second edition, this textbook serves as an introduction toprobability and statistics for non-mathematics majors who do not need theexhaustive detail and mathematical depth provided in more comprehensivetreatments of the subject. The presentation covers the mathematical laws ofrandom phenomena, including discrete and continuous random variables,expectation and variance, and common probability distributions such as thebinomial, Poisson, and normal distributions. More classical examples such asMontmort's problem, the ballot problem, and Bertrand’s paradox are nowincluded, along with applications such as the Maxwell-Boltzmann andBose-Einstein distributions in physics.Keyfeatures in new edition:* 35 newexercises* Expanded sectionon the algebra of sets *Expanded chapters on probabilities to include more classical examples* Newsection on regression* Onlineinstructors' manual containing solutions to all exercises
Описание: Serves as a comprehensive treatment of the fundamentals of probability and statistical inference. This textbook helps readers to advance to topics such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. It discusses modes of convergence of sequences of random variables.
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.
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.
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