Probability and Statistics for Computer Scientists
2nd Edition
Published on 5. August 2013
473 pages
978-1-4987-6060-7 (ISBN)
Description
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating 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 o
Reviews / Votes
"... an immensely readable text intended for junior undergraduate to beginning graduate students in computer-related fields, though it could be suitable for any calculus-based probability and/or mathematical statistics course. ... the book is well written, and very well suited to the target audience-individuals in computer-related fields. Through examples and exercises, the author does an excellent job demonstrating how probability and statistics are used in computer-related fields. The text could also be used for a standalone probability course or a two-semester probability and mathematical statistics sequence for mathematics and statistics students."-The American Statistician, February 2015
"The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter in statistics. Since the author has taken great care to select examples that are interesting and practical for computer scientists, the book should hold special appeal for that group. ... The content is illustrated with numerous figures, and concludes with appendices and an index. The book is erudite and demands a reader with a firm background in calculus. It could work well as a required text for an advanced undergraduate or graduate course."
-James Van Speybroeck, Computing Reviews, January 2014
Praise for the First Edition:"... students of all majors will benefit from the author's fine presentation of applied probability models and computer simulation. I am seriously considering adopting it for a [probability-oriented course] ... the chapters on simulation and applied probability models are truly outstanding ..."
-Matthew A. Carlton, The American Statistician, August 2008
"...well-organized text seems designed as a gentle introduction to the mathematics of probability and statistics. ...helpful diagrams...surprisingly detailed."
-John Maindonald, International Statistical Review, Vol. 75, No. 2, 2007
"... an ideal textbook for computer science students. ... This book is primarily intended for junior undergraduate to beginning graduate level students majoring in computer-related fields. It can also be used by electrical engineering, mathematics, statistics, actuarial science, and other majors for a standard introductory statistics course. Graduate students can use this book to prepare for probability-based courses such as queuing theory, artificial neural networks, and computer performance. Overall, this well-written text can be used as a standard reference on probability and statistical methods, simulation and modeling tools."
-Journal of the Royal Statistical Society
"The book represents a good reference to all who are interested in statistics, modeling stochastic processes, and computer simulation. ... The book's material is invaluable and presented with clarity ..."
-Journal of Applied Statistics, 2007
More details
Edition
2nd edition
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Edition type
New edition
File size
3,95 MB
ISBN-13
978-1-4987-6060-7 (9781498760607)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Michael Baron
Probability and Statistics for Computer Scientists
Book
08/2013
2nd Edition
Taylor & Francis
€106.45
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Person
Michael Baron is a professor of statistics at the University of Texas at Dallas. 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 International Society for Bayesian Analysis, and an associate editor of the Journal of Sequential Analysis. In 2007, he was awarded the Abraham Wald Prize in Sequential Analysis. His research focuses on the use of sequential analysis, change-point detection, and Bayesian inference in epidemiology, clinical trials, cyber security, energy, finance, and semiconductor manufacturing. He received a Ph.D. in statistics from the University of Maryland.
Content
Introduction and Overview. Probability and Random Variables: Probability. Discrete Random Variables and Their Distributions. Continuous Distributions. Computer Simulations and Monte Carlo Methods. Stochastic Processes: Stochastic Processes. Queuing Systems. Statistics: Introduction to Statistics. Statistical Inference I. Statistical Inference II. Regression. Appendix. Index.
