Computing Science And Statistics

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Probability and Statistics for Computer Science

Author : David Forsyth
Publisher : Springer
ISBN 13 : 3319644106
Total Pages : 367 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Probability and Statistics for Computer Science by : David Forsyth

Download or read book Probability and Statistics for Computer Science written by David Forsyth and published by Springer. This book was released on 2017-12-13 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features: • A treatment of random variables and expectations dealing primarily with the discrete case. • A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. • A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. • A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. • A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. • A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. • A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.

An Introduction to Statistical Computing

Author : Jochen Voss
Publisher : John Wiley & Sons
ISBN 13 : 1118728025
Total Pages : 322 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis An Introduction to Statistical Computing by : Jochen Voss

Download or read book An Introduction to Statistical Computing written by Jochen Voss and published by John Wiley & Sons. This book was released on 2013-08-28 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course.

Elements of Statistical Computing

Author : R.A. Thisted
Publisher : Routledge
ISBN 13 : 1351452754
Total Pages : 448 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Elements of Statistical Computing by : R.A. Thisted

Download or read book Elements of Statistical Computing written by R.A. Thisted and published by Routledge. This book was released on 2017-10-19 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

Probability, Statistics, and Queueing Theory

Author : Arnold O. Allen
Publisher : Academic Press
ISBN 13 : 0080571050
Total Pages : 768 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Probability, Statistics, and Queueing Theory by : Arnold O. Allen

Download or read book Probability, Statistics, and Queueing Theory written by Arnold O. Allen and published by Academic Press. This book was released on 2014-06-28 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edition includes a new chapter on regression as well as more than twice as many exercises at the end of each chapter. While the emphasis is the same as in the first edition, this new book makes more extensive use of available personal computer software, such as Minitab and Mathematica.

Computing in Statistical Science through APL

Author : Francis John Anscombe
Publisher : Springer Science & Business Media
ISBN 13 : 1461394503
Total Pages : 440 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Computing in Statistical Science through APL by : Francis John Anscombe

Download or read book Computing in Statistical Science through APL written by Francis John Anscombe and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: A t the terminal seated, the answering tone: pond and temple bell. ODAY as in the past, statistical method is profoundly affected by T resources for numerical calculation and visual display. The main line of development of statistical methodology during the first half of this century was conditioned by, and attuned to, the mechanical desk calculator. Now statisticians may use electronic computers of various kinds in various modes, and the character of statistical science has changed accordingly. Some, but not all, modes of modern computation have a flexibility and immediacy reminiscent of the desk calculator. They preserve the virtues of the desk calculator, while immensely exceeding its scope. Prominent among these is the computer language and conversational computing system known by the initials APL. This book is addressed to statisticians. Its first aim is to interest them in using APL in their work-for statistical analysis of data, for numerical support of theoretical studies, for simulation of random processes. In Part A the language is described and illustrated with short examples of statistical calculations. Part B, presenting some more extended examples of statistical analysis of data, has also the further aim of suggesting the interplay of computing and theory that must surely henceforth be typical of the develop ment of statistical science.

Statistical Computing with R

Author : Maria L. Rizzo
Publisher : CRC Press
ISBN 13 : 1420010719
Total Pages : 412 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Statistical Computing with R by : Maria L. Rizzo

Download or read book Statistical Computing with R written by Maria L. Rizzo and published by CRC Press. This book was released on 2007-11-15 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditiona

Probability and Statistics for Computer Science

Author : James L. Johnson
Publisher : John Wiley & Sons
ISBN 13 : 1118165969
Total Pages : 764 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Probability and Statistics for Computer Science by : James L. Johnson

Download or read book Probability and Statistics for Computer Science written by James L. Johnson and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Computing with Data

Author : Guy Lebanon
Publisher : Springer
ISBN 13 : 3319981498
Total Pages : 576 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Computing with Data by : Guy Lebanon

Download or read book Computing with Data written by Guy Lebanon and published by Springer. This book was released on 2018-11-28 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

Computing Science and Statistics

Author : Connie Page
Publisher :
ISBN 13 : 9783540977193
Total Pages : 582 pages
Book Rating : 4.9/5 (771 download)

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Book Synopsis Computing Science and Statistics by : Connie Page

Download or read book Computing Science and Statistics written by Connie Page and published by . This book was released on 1992-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applications in Statistical Computing

Author : Nadja Bauer
Publisher : Springer Nature
ISBN 13 : 3030251470
Total Pages : 336 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Applications in Statistical Computing by : Nadja Bauer

Download or read book Applications in Statistical Computing written by Nadja Bauer and published by Springer Nature. This book was released on 2019-10-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.

Computer Age Statistical Inference, Student Edition

Author : Bradley Efron
Publisher : Cambridge University Press
ISBN 13 : 1108915876
Total Pages : 514 pages
Book Rating : 4.1/5 (89 download)

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Book Synopsis Computer Age Statistical Inference, Student Edition by : Bradley Efron

Download or read book Computer Age Statistical Inference, Student Edition written by Bradley Efron and published by Cambridge University Press. This book was released on 2021-06-17 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.

Computing Science and Statistics

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (638 download)

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Book Synopsis Computing Science and Statistics by :

Download or read book Computing Science and Statistics written by and published by . This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Probability and Statistics for Computer Scientists

Author : Michael Baron
Publisher : CRC Press
ISBN 13 : 1420011421
Total Pages : 427 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Probability and Statistics for Computer Scientists by : Michael Baron

Download or read book Probability and Statistics for Computer Scientists written by Michael Baron and published by CRC Press. This book was released on 2018-11-14 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface

Author : W. F. Eddy
Publisher : Springer Science & Business Media
ISBN 13 : 1461394643
Total Pages : 375 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface by : W. F. Eddy

Download or read book Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface written by W. F. Eddy and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 13th Symposium on the Interface continued this series after a one year pause. The objective of these symposia is to provide a forum for the interchange of ideas of common concern to computer scientists and statisticians. The sessions of the 13th Symposium were held in the Pittsburgh Hilton Hotel, Gateway Center, Pittsburgh. Following established custom the 13th Symposium had organized workshops on various topics of interest to participants. The workshop format allowed the invited speakers to present their material variously as formal talks, tutorial sessions and open discussion. The Symposium schedule was also the customary one. Registration opened in late afternoon of March 11, 1981 and continued during the opening mixer held that evening: The formal opening of the Symposium was on the morning of March 12. The opening remarks were followed by Bradley Efron's address "Statistical Theory and the Computer." The rest of the daily schedule was three concurrent workshops in the morning and three in the afternoon with contributed poster sessions during the noon break. Additionally there were several commercial displays and guided tours of Carnegie-Mellon University's Computer Center, Computer Science research facilities, and Robotics Institute.

Computational Statistics in Data Science

Author : Richard A. Levine
Publisher : John Wiley & Sons
ISBN 13 : 1119561086
Total Pages : 672 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Computational Statistics in Data Science by : Richard A. Levine

Download or read book Computational Statistics in Data Science written by Richard A. Levine and published by John Wiley & Sons. This book was released on 2022-03-23 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ein unverzichtbarer Leitfaden bei der Anwendung computergestützter Statistik in der modernen Datenwissenschaft In Computational Statistics in Data Science präsentiert ein Team aus bekannten Mathematikern und Statistikern eine fundierte Zusammenstellung von Konzepten, Theorien, Techniken und Praktiken der computergestützten Statistik für ein Publikum, das auf der Suche nach einem einzigen, umfassenden Referenzwerk für Statistik in der modernen Datenwissenschaft ist. Das Buch enthält etliche Kapitel zu den wesentlichen konkreten Bereichen der computergestützten Statistik, in denen modernste Techniken zeitgemäß und verständlich dargestellt werden. Darüber hinaus bietet Computational Statistics in Data Science einen kostenlosen Zugang zu den fertigen Einträgen im Online-Nachschlagewerk Wiley StatsRef: Statistics Reference Online. Außerdem erhalten die Leserinnen und Leser: * Eine gründliche Einführung in die computergestützte Statistik mit relevanten und verständlichen Informationen für Anwender und Forscher in verschiedenen datenintensiven Bereichen * Umfassende Erläuterungen zu aktuellen Themen in der Statistik, darunter Big Data, Datenstromverarbeitung, quantitative Visualisierung und Deep Learning Das Werk eignet sich perfekt für Forscher und Wissenschaftler sämtlicher Fachbereiche, die Techniken der computergestützten Statistik auf einem gehobenen oder fortgeschrittenen Niveau anwenden müssen. Zudem gehört Computational Statistics in Data Science in das Bücherregal von Wissenschaftlern, die sich mit der Erforschung und Entwicklung von Techniken der computergestützten Statistik und statistischen Grafiken beschäftigen.

Computing Science and Statistics

Author : Connie Page
Publisher : Springer Science & Business Media
ISBN 13 : 1461228565
Total Pages : 595 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Computing Science and Statistics by : Connie Page

Download or read book Computing Science and Statistics written by Connie Page and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interface '90 is the continuation of an ext!remely successful symposium series. The series has provided a forum for the interaction of professionals in statistics, computing science, and in numerical methods, wherein they may discuss a wide range of topics at the interface of these disciplines. This, the 22nd Symposium on the Interface: Computing Science and Statistics, was held 16-19 May, 1990 at the Kellogg Center on the campus of Michigan State University and is the third Symposium to be held under the recently organized Interface Foundation of North America. The Interface Board of Directors consists of the nine most recent Symposium Chairs: James E. Gentle, Lynne Billard, David M. Allen, Thomas J. Boardman, Richard M. Heiberger, Edward J. Wegman, Linda Malone, Raoul LePage, and Jon Kettenring. The officers of the Interface are William Eddy, Board Chairman and Executive Director; Edward Wegman, President and Treasurer; Lynne Billard, Secretary. My valued colleague Connie Page, Editor of this Proceedings Volume and generally bright and hardworking person, has organizational skills of a higher order which were successfully brought into play during many critical junctures not strictly connected with the Proceedings. Edward Wegman, Barbara Barringer, Bill Eddy, and George Styan all pitched in with useful information on numerous occasions. Our Keynote Speaker, Peter G. Hall and Plenary Speakers David L. Donoho, Jerome H. Friedman (who also gave a short course), Bruce Hajek, John Skilling, and C. F.

Computer Age Statistical Inference

Author : Bradley Efron
Publisher : Cambridge University Press
ISBN 13 : 1108107958
Total Pages : 496 pages
Book Rating : 4.1/5 (81 download)

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Book Synopsis Computer Age Statistical Inference by : Bradley Efron

Download or read book Computer Age Statistical Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2016-07-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.