Applied Probability Computer Science
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| Author | : Arnold O. Allen |
| Publisher | : Gulf Professional Publishing |
| Total Pages | : 776 |
| Release | : 1990-08-28 |
| Genre | : Computers |
| ISBN | : 9780120510511 |
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.
| Author | : Dimitri Bertsekas |
| Publisher | : Athena Scientific |
| Total Pages | : 544 |
| Release | : 2008-07-01 |
| Genre | : Mathematics |
| ISBN | : 188652923X |
An intuitive, yet precise introduction to probability theory, stochastic processes, statistical inference, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students, and for a leading online class on the subject. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains a number of more advanced topics, including transforms, sums of random variables, a fairly detailed introduction to Bernoulli, Poisson, and Markov processes, Bayesian inference, and an introduction to classical statistics. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis is explained intuitively in the main text, and then developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems.
| Author | : Kenneth Lange |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 378 |
| Release | : 2008-01-17 |
| Genre | : Mathematics |
| ISBN | : 0387227113 |
Despite the fears of university mathematics departments, mathematics educat,ion is growing rather than declining. But the truth of the matter is that the increases are occurring outside departments of mathematics. Engineers, computer scientists, physicists, chemists, economists, statis- cians, biologists, and even philosophers teach and learn a great deal of mathematics. The teaching is not always terribly rigorous, but it tends to be better motivated and better adapted to the needs of students. In my own experience teaching students of biostatistics and mathematical bi- ogy, I attempt to convey both the beauty and utility of probability. This is a tall order, partially because probability theory has its own vocabulary and habits of thought. The axiomatic presentation of advanced probability typically proceeds via measure theory. This approach has the advantage of rigor, but it inwitably misses most of the interesting applications, and many applied scientists rebel against the onslaught of technicalities. In the current book, I endeavor to achieve a balance between theory and app- cations in a rather short compass. While the combination of brevity apd balance sacrifices many of the proofs of a rigorous course, it is still cons- tent with supplying students with many of the relevant theoretical tools. In my opinion, it better to present the mathematical facts without proof rather than omit them altogether.
| Author | : Mario Lefebvre |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 364 |
| Release | : 2007-04-03 |
| Genre | : Mathematics |
| ISBN | : 0387285059 |
This book moves systematically through the topic of applied probability from an introductory chapter to such topics as random variables and vectors, stochastic processes, estimation, testing and regression. The topics are well chosen and the presentation is enriched by many examples from real life. Each chapter concludes with many original, solved and unsolved problems and hundreds of multiple choice questions, enabling those unfamiliar with the topics to master them. Additionally appealing are historical notes on the mathematicians mentioned throughout, and a useful bibliography. A distinguishing character of the book is its thorough and succinct handling of the varied topics.
| Author | : Ralph L. Disney |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 496 |
| Release | : 2013-03-14 |
| Genre | : Science |
| ISBN | : 1461257980 |
| Author | : Kishor S. Trivedi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 881 |
| Release | : 2016-07-11 |
| Genre | : Computers |
| ISBN | : 0471460818 |
An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications Second edition now also available in Paperback. This updated and revised edition of the popular classic first edition 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. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
| Author | : Ralph L. Disney |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 513 |
| Release | : 2013-03-07 |
| Genre | : Science |
| ISBN | : 1461257913 |
These two volumes are the Proceedings of the first special interest meeting instigated and organized by the joint Technical Section and College in Applied Probability of ORSA and THlS. This meeting, which took place January 5-7, 1981 at Florida Atlantic University in Boca Raton, Florida, had the same name as these Proceedings: Applied Probability-Computer Science, the Interface. The goal of that conference was to achieve a meeting of, and a cross fertilization between, two groups of researchers who, from different starting points, had come to work on similar problems, often developing similar methodologies and tools. One of these groups are the applied probabilists, many of whom consider their field an offspring of mathematics, and who find their motivation in many areas of application. The other is that group of computer scientists who, over the years, have found an increasing need in their work for the use of probabilistic models. The most visible area of common methodology between these two groups is networks of queues, Hhich by itself could have been the theme of an entire conference. FunctionQl areas which are, or are becoming, sources of exciting problems are computer performance analysis, data base analysis, analysis of communication protocols, data networks, and mixed voice-data telephone networks. The reader can add to this list by going through the papers in these Proceedings.
| Author | : Richard Martin Feldman |
| Publisher | : Brooks/Cole |
| Total Pages | : 328 |
| Release | : 1996 |
| Genre | : Mathematics |
| ISBN | : |
In this book, Feldman and Valdez-Flores present applied probability and stochastic processes in an elementary but mathematically precise manner, with numerous examples and exercises to illustrate the range of engineering and science applications for the concepts. The book is designed to give the reader an intuitive understanding of probabilistic reasoning, in addition to an understanding of mathematical concepts and principles. Unique features of the book include a self-contained chapter on simulation (Chapter 3) and early introduction of Markov chains.
| Author | : David Forsyth |
| Publisher | : Springer |
| Total Pages | : 374 |
| Release | : 2017-12-13 |
| Genre | : Computers |
| ISBN | : 3319644106 |
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.
| Author | : Michael Baron |
| Publisher | : CRC Press |
| Total Pages | : 475 |
| Release | : 2013-08-05 |
| Genre | : Mathematics |
| ISBN | : 1439875901 |
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.
