Introduction to Probability for Computing

Mor Harchol-Balter

ISBN 10: 1009309072 / ISBN 13: 9781009309073

Published by Cambridge University Pr. Sep 2023, 2023

About this Item

Neuware -Learn about probability as it is used in computer science with this rigorous, yet highly accessible, undergraduate textbook. Fundamental probability concepts are explained in depth, prerequisite mathematics is summarized, and a wide range of computer science applications is described. Throughout, the material is presented in a 'question and answer' style designed to encourage student engagement and understanding. Replete with almost 400 exercises, real-world computer science examples, and covering a wide range of topics from simulation with computer science workloads, to statistical inference, to randomized algorithms, to Markov models and queues, this interactive text is an invaluable learning tool whether your course covers probability with statistics, with stochastic processes, with randomized algorithms, or with simulation. The teaching package includes solutions, lecture slides, and lecture notes for students. 550 pp. Englisch.

Seller Inventory # 9781009309073

Bibliographic Details

• Title: Introduction to Probability for Computing
• Publisher: Cambridge University Pr. Sep 2023
• Publication Date: 2023
• Language: English
• ISBN 10: 1009309072
• ISBN 13: 9781009309073
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 35D millimeters 250 millimeters width by 175 millimeters height by 35 millimeters depth
• Weight: 1157 grams

About this title

Synopsis

Learn about probability as it is used in computer science with this rigorous, yet highly accessible, undergraduate textbook. Fundamental probability concepts are explained in depth, prerequisite mathematics is summarized, and a wide range of computer science applications is described. Throughout, the material is presented in a “question and answer” style designed to encourage student engagement and understanding. Replete with almost 400 exercises, real-world computer science examples, and covering a wide range of topics from simulation with computer science workloads, to statistical inference, to randomized algorithms, to Markov models and queues, this interactive text is an invaluable learning tool whether your course covers probability with statistics, with stochastic processes, with randomized algorithms, or with simulation. The teaching package includes solutions, lecture slides, and lecture notes for students.

About the Author

Mor Harchol-Balter is the Bruce J. Nelson Professor of Computer Science at Carnegie Mellon University. She is a Fellow of both ACM and IEEE. She has received numerous teaching awards, including the Herbert A. Simon Award for teaching excellence at CMU. She is also the author of the popular textbook Performance Analysis and Design of Computer Systems (Cambridge, 2013).