Download EBOOK Probability and Statistics for Computer Scientists PDF for free
 
Category: Computing
The author of the book: Michael Baron
Format files: PDF, EPUB, TXT, DOCX
The size of the: 11.52 MB
Language: English
ISBN13: 9781439875902
Edition: Chapman & Hall/CRC
Date of issue: 12 September 2013

Description of the book "Probability and Statistics for Computer Scientists":
StudentFriendly 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 probabilitybased courses. Written in a lively style with simple language, this classroomtested book can now be used in both one and twosemester courses.
New to the Second Edition * Axiomatic introduction of probability * Expanded coverage of statistical inference, including standard PDF errors of estimates and their estimation, inference about variances, chisquare 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 InDepth yet Accessible Treatment of Computer ScienceRelated 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 ePub 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.
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Michael Baron
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