Probability and Statistics for Computer Scientists [Hardcover]

Michael Baron (Author)

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Hardcover, Dec 13 2006	CDN $96.04	--	--
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Product Details

Hardcover: 426 pages
Publisher: Chapman and Hall/CRC; 1 edition (Dec 13 2006)
Language: English
ISBN-10: 1584886412
ISBN-13: 978-1584886419
Product Dimensions: 24.9 x 16.4 x 3.3 cm
Shipping Weight: 612 g
Amazon Bestsellers Rank: #1,715,110 in Books (See Top 100 in Books)

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Product Description

In modern computer science, software engineering, and other fields, the need arises to make decisions under uncertainty. Presenting probability and statistical methods, simulation techniques, and modeling tools, Probability and Statistics for Computer Scientists helps students solve problems and make optimal decisions in uncertain conditions, select stochastic models, compute probabilities and forecasts, and evaluate performance of computer systems and networks.

After introducing probability and distributions, this easy-to-follow textbook provides two course options. The first approach is a probability-oriented course that begins with stochastic processes, Markov chains, and queuing theory, followed by computer simulations and Monte Carlo methods. The second approach is a more standard, statistics-emphasized course that focuses on statistical inference, estimation, hypothesis testing, and regression. Assuming one or two semesters of college calculus, the book is illustrated throughout with numerous examples, exercises, figures, and tables that stress direct applications in computer science and software engineering. It also provides MATLAB^® codes and demonstrations written in simple commands that can be directly translated into other computer languages.

By the end of this course, advanced undergraduate and beginning graduate students should be able to read a word problem or a corporate report, realize the uncertainty involved in the described situation, select a suitable probability model, estimate and test its parameters based on real data, compute probabilities of interesting events and other vital characteristics, and make appropriate conclusions and forecasts.

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Amazon.com: 5.0 out of 5 stars (1 customer review)

5 of 5 people found the following review helpful

5.0 out of 5 stars I can't say enough good things about this book, Dec 22 2008

By Joshua Davies - Published on Amazon.com

This review is from: Probability and Statistics for Computer Scientists (Hardcover)

This book was perfect. I picked it up when I was working on my master's thesis - I kept running into probability and statistics terminology with which I was not familiar, so I knew I needed a refresher. Fortunately for me, this book turned out to be the perfect choice. It's written as a textbook, of course, but I found it extremely useful as a self-teaching tool as well as a handy reference.

The author doesn't hold back, though - you'll need to have a pretty good grasp of calculus to follow all of the text (although you could probably get something out of it without any exposure to calculus). He even makes use of what I consider fairly advanced calculus such as partial differentiation and integration by parts. Fortunately, there's an appendix that covers the relevant math background - for example, I had never been exposed to integration by parts, but I was able to figure it out from the explanation in the appendix. He also makes use of some linear algebra (matrix operations) in chapters 5 and 10, but again, the appendix covers the fundamentals of its use in the book.

This is, of course, a math book, and I find the best indicator of the value of a math book to be in its exercises. Here, again, I found the exercises to be perfect for what I needed. They covered the material fully, ranged from simple "did you understand the text" to complex "prove such-and-such", but all of them could be solved based on the contents of the chapter in question. Also, the book has answers to selected exercises (a common omission in recent math books which infuriates me), although I would have appreciated a few more - only about a third of the exercises have answers for self-checking.

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