Probability and Statistics for Computer Scientists

The Third Edition of Probability and Statistics for Computer Scientists is an updated and comprehensive textbook that covers fundamental concepts, stochastic modeling, simulation, queuing, and statistical data analysis. It is written in a lively style with simple language and includes R and MATLAB codes. The book is suitable for one- or two-semester courses and has applications in computer science, software engineering, telecommunications, and related areas.

Format: Hardback
Length: 486 pages
Publication date: 02 July 2019
Publisher: Taylor & Francis Ltd

The author has done an exceptional job in preparing the second edition of Probability and Statistics for Computer Scientists. Their extensive research on the statistical tools required for the unique challenges faced by computer scientists is evident throughout the book. The author has taken great care in selecting examples that are both interesting and practical, making it an invaluable resource for computer scientists.

The content is well-illustrated with numerous figures, enhancing the understanding of the topics discussed. Additionally, the book concludes with appendices and an index, providing valuable supplementary materials for further reference. This book is characterized by its erudite nature, making it suitable as a required text for advanced undergraduate or graduate courses.

The third edition of Probability and Statistics for Computer Scientists is a comprehensive textbook that aims to help students grasp fundamental concepts of probability and statistics, as well as general methods of stochastic modeling, simulation, queuing, and statistical data analysis. Written in a lively style with simple language, the book is designed to be accessible to students with a range of backgrounds.

One of the notable features of this edition is its expanded coverage of statistical inference and data analysis. The book provides a comprehensive introduction to estimation and testing, including Bayesian approach, multivariate regression, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap. Numerous motivating examples and exercises, including computer projects, are included to reinforce the concepts and help students apply their knowledge.

In addition to its theoretical aspects, the book also emphasizes the practical applications of probability and statistics in computer science, software engineering, telecommunications, and related areas. The author has included numerous real-world examples and case studies to illustrate the importance of these topics in modern computing.

The text is well-organized, with each chapter presenting a clear and concise overview of the topics covered. The explanations are accompanied by detailed examples and R codes in parallel to MATLAB, making it easier for students to understand and apply the concepts. The book also includes a comprehensive glossary and an index, providing further assistance to students.

Overall, Probability and Statistics for Computer Scientists, Third Edition is an excellent textbook that caters to the needs of students studying computer science, computer engineering, software engineering, and related fields. Its comprehensive coverage, engaging writing style, and practical applications make it an invaluable resource for anyone seeking to enhance their understanding of probability and statistics. Whether used as a primary text or as a supplementary material, this book is sure to provide students with the knowledge and skills necessary to succeed in their academic and professional endeavors.

Weight: 1056g
Dimension: 184 x 260 x 36 (mm)
ISBN-13: 9781138044487
Edition number: 3 New edition