Probabilistic And Statistical Methods In Computer Science
DOWNLOAD
Download Probabilistic And Statistical Methods In Computer Science PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Probabilistic And Statistical Methods In Computer Science book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Probabilistic And Statistical Methods In Computer Science
DOWNLOAD
Author : Jean-François Mari
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Probabilistic And Statistical Methods In Computer Science written by Jean-François Mari and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
Probabilistic and Statistical Methods in Computer Science
Probability And Statistics For Computer Scientists
DOWNLOAD
Author : Michael Baron
language : en
Publisher: CRC Press
Release Date : 2018-11-14
Probability And Statistics For Computer Scientists written by Michael Baron and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-14 with Mathematics categories.
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
Probabilistic And Statistical Methods In Cryptology
DOWNLOAD
Author : Daniel Neuenschwander
language : en
Publisher:
Release Date : 2014-01-15
Probabilistic And Statistical Methods In Cryptology written by Daniel Neuenschwander and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Probabilistic And Statistical Methods In Cryptology
DOWNLOAD
Author : Daniel Neuenschwander
language : en
Publisher: Springer
Release Date : 2004-06-08
Probabilistic And Statistical Methods In Cryptology written by Daniel Neuenschwander and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-08 with Computers categories.
Cryptology nowadays is one of the most important areas of applied mathematics, building on deep results and methods from various areas of mathematics. This text is devoted to the study of stochastic aspects of cryptology. Besides classical topics from cryptology, the author presents chapters on probabilistic prime number tests, factorization with quantum computers, random-number generators, pseudo-random-number generators, information theory, and the birthday paradox and meet-in-the-middle attack. In the light of the vast literature on stochastic results relevant for cryptology, this book is intended as an invitation and introduction for students, researchers, and practitioners to probabilistic and statistical issues in cryptology.
Introduction To Probabilistic And Statistical Methods With Examples In R
DOWNLOAD
Author : Katarzyna Stapor
language : en
Publisher: Springer Nature
Release Date : 2020-05-22
Introduction To Probabilistic And Statistical Methods With Examples In R written by Katarzyna Stapor and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with Mathematics categories.
This book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.
Probability And Statistics
DOWNLOAD
Author : J. Susan Milton
language : en
Publisher: McGraw-Hill Europe
Release Date : 2012-11
Probability And Statistics written by J. Susan Milton and has been published by McGraw-Hill Europe this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11 with Electronic data processing categories.
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.
Probability And Statistics For Computer Science
DOWNLOAD
Author : James L. Johnson
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-09
Probability And Statistics For Computer Science written by James L. Johnson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-09 with Mathematics categories.
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
Probability And Statistics For Computer Scientists Second Edition
DOWNLOAD
Author : Michael Baron
language : en
Publisher: CRC Press
Release Date : 2013-08-05
Probability And Statistics For Computer Scientists Second Edition written by Michael Baron and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-05 with Mathematics categories.
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® 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.
Statistical Methods In Software Engineering
DOWNLOAD
Author : Nozer D. Singpurwalla
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Statistical Methods In Software Engineering written by Nozer D. Singpurwalla and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
In establishing a framework for dealing with uncertainties in software engineering, and for using quantitative measures in related decision-making, this text puts into perspective the large body of work having statistical content that is relevant to software engineering. Aimed at computer scientists, software engineers, and reliability analysts who have some exposure to probability and statistics, the content is pitched at a level appropriate for research workers in software reliability, and for graduate level courses in applied statistics computer science, operations research, and software engineering.
Probability And Statistics For Computer Science
DOWNLOAD
Author : David Forsyth
language : en
Publisher: Springer
Release Date : 2017-12-13
Probability And Statistics For Computer Science written by David Forsyth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-13 with Computers categories.
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.