Probability and Statistics for Computer Scientists by Michael Baron: Starting with the basics of probability, this text leads readers to computer simulations, statistical inference, and regression. These areas are heavily utilized in modern computer science, computer engineering, software engineering, and related fields.
Probability and Statistics for Computer Scientists is primarily for junior undergraduate to beginner level students majoring in computer science engineering, artificial intelligence, information systems, information technology, telecommunications, etc. At an equivalent time, it can be employed by EE , mathematics, statistics, science , and other majors for a standard calculus-based introductory statistics course.
Standard topics in probability and statistics are in Chapters 1–4 and 8–9. Graduate students can use this book to organize for probability-based courses like queuing theory, artificial neural networks, computer performance, etc. The book also can be used as a typical reference on probability and statistical methods, simulation, and modeling tools.
The text is especially recommended for a one-semester course with several open-end options available. Probability-oriented course. Proceed to Chapters 6–7 for Stochastic Processes, Markov Chains, and Queuing Theory.
Author of “Probability and Statistics for Computer Scientists” is Michael Baron
Probability and Statistics for Computer Scientists by Michael Baron: Table of Content
- Introduction and Overview
- Probability and Random Variables
- Stochastic Processes
- Statistics
Conclusion
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