ISBN: 9781138044487 - probability and statistics for computer scientists (24 resultados)

Condición: good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.

Hardcover. Condición: Fair. Book in Fair condition.

Hardcover. Condición: Good. Book in Good condition.

Condición: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condición: New.

hardcover. Condición: New. 3rd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Condición: New. 2019. 3rd Edition. Hardcover. . . . . .

Condición: New.

Condición: New. pp. 491.

Condición: New. pp. 491.

Hardback. Condición: New. 3rd. Praise for the Second Edition:"The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and . could work well as a required text for an advanced undergraduate or graduate course." ---Computing ReviewsProbability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB, this classroom-tested book can be used for one- or two-semester courses.Features:Axiomatic introduction of probabilityExpanded coverage of statistical inference and data analysis, including estimation and testing, Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrapNumerous motivating examples and exercises including computer projectsFully annotated R codes in parallel to MATLABApplications in computer science, software engineering, telecommunications, and related areasIn-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting 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).…

Condición: New. 2019. 3rd Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Condición: New. pp. 491.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Hardcover. Condición: Brand New. 3rd edition. 465 pages. 10.00x7.00x1.25 inches. In Stock.

Hardback. Condición: New. 3rd. Praise for the Second Edition:"The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and . could work well as a required text for an advanced undergraduate or graduate course." ---Computing ReviewsProbability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB, this classroom-tested book can be used for one- or two-semester courses.Features:Axiomatic introduction of probabilityExpanded coverage of statistical inference and data analysis, including estimation and testing, Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrapNumerous motivating examples and exercises including computer projectsFully annotated R codes in parallel to MATLABApplications in computer science, software engineering, telecommunications, and related areasIn-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting 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).…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Michael Baron is a professor of statistics at the American University in Washington, DC. He has published two books and numerous research articles and book chapters. Dr. Baron is a fellow of the American Statistical Association, a member of the Internati.…

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Praise for the Second Edition:'The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and . could work well as a required text for an advanced undergraduate or graduate course.' ---Computing ReviewsProbability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB, this classroom-tested book can be used for one- or two-semester courses.Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis, including estimation and testing, Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science, software engineering, telecommunications, and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting 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). 486 pp. Englisch.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Praise for the Second Edition:'The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and . could work well as a required text for an advanced undergraduate or graduate course.' ---Computing ReviewsProbability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB, this classroom-tested book can be used for one- or two-semester courses.Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis, including estimation and testing, Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science, software engineering, telecommunications, and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting 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).…