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Practical Discrete Mathematics

Practical Discrete Mathematics

By : Ryan T. White, Ray
4.6 (17)
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Practical Discrete Mathematics

Practical Discrete Mathematics

4.6 (17)
By: Ryan T. White, Ray

Overview of this book

Discrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. The knowledge of discrete math concepts will help you understand the algorithms, binary, and general mathematics that sit at the core of data-driven tasks. Practical Discrete Mathematics is a comprehensive introduction for those who are new to the mathematics of countable objects. This book will help you get up to speed with using discrete math principles to take your computer science skills to a more advanced level. As you learn the language of discrete mathematics, you’ll also cover methods crucial to studying and describing computer science and machine learning objects and algorithms. The chapters that follow will guide you through how memory and CPUs work. In addition to this, you’ll understand how to analyze data for useful patterns, before finally exploring how to apply math concepts in network routing, web searching, and data science. By the end of this book, you’ll have a deeper understanding of discrete math and its applications in computer science, and be ready to work on real-world algorithm development and machine learning.
Table of Contents (17 chapters)
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1
Part I – Basic Concepts of Discrete Math
7
Part II – Implementing Discrete Mathematics in Data and Computer Science
12
Part III – Real-World Applications of Discrete Mathematics

Chapter 5: Elements of Discrete Probability

Probability is the study of randomness, chance, and uncertainty. We experience randomness all the time–from the weather to the stock market to the results of sporting events and elections. We can never predict these things with certainty, but we can make reliable statements about the likelihood (or probability) of events occurring through careful study of patterns in the uncertainty and variables that may affect it.

The type of probability that's most important to discrete mathematics and computer science is to do with, of course, discrete sets. In this chapter, after establishing how probability works in the general sense, we will present elements of combinatorial probability. This is important in situations where each resulting outcome of a random experiment is equally likely, so that the chance that the result is in a certain set of outcomes which depends on counting the size of the set. Then, we will look at conditional...

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Practical Discrete Mathematics
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