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Information Theory and Statistics: A Tutorial

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Information Theory and Statistics: A Tutorial is concerned with applications of information theory concepts in statistics, in the finite alphabet setting. The topics covered include large deviations, hypothesis testing, maximum likelihood estimation in exponential families, analysis of contingency tables, and iterative algorithms with an "information geometry" background. Also, an introduction is provided to the theory of universal coding, and to statistical inference via the minimum description length principle motivated by that theory. The tutorial does not assume the reader has an in-depth knowledge of Information Theory or statistics. As such, Information Theory and Statistics: A Tutorial, is an excellent introductory text to this highly-important topic in mathematics, computer science and electrical engineering. It provides both students and researchers with an invaluable resource to quickly get up to speed in the field.
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The Bartender's Best Friend: A Complete Guide to Cocktails, Martinis, and Mixed Drinks
The Bartender's Best Friend: A Complete Guide to Cocktails, Martinis, and Mixed Drinks

The ultimate companion for mixing drinks and tending bar

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Schaum's Outline of Advanced Calculus, Second Edition
Schaum's Outline of Advanced Calculus, Second Edition
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Abdominal Ultrasound: How, Why and When
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Developers don't get to spend a lot of time thinking about design, but many secretly wish they knew how to make their applications look just a little bit better. This book takes you on a journey through a web site redesign, where you'll learn the basic concepts of design, color theory, typography, and accessibility. You'll learn how to...

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