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The Statistics and Calculus with Python Workshop

You're reading from   The Statistics and Calculus with Python Workshop A comprehensive introduction to mathematics in Python for artificial intelligence applications

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209763
Length 740 pages
Edition 1st Edition
Languages
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Authors (6):
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Ajinkya Sudhir Kolhe Ajinkya Sudhir Kolhe
Author Profile Icon Ajinkya Sudhir Kolhe
Ajinkya Sudhir Kolhe
Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
Marios Tsatsos Marios Tsatsos
Author Profile Icon Marios Tsatsos
Marios Tsatsos
Alexander Joseph Sarver Alexander Joseph Sarver
Author Profile Icon Alexander Joseph Sarver
Alexander Joseph Sarver
Peter Farrell Peter Farrell
Author Profile Icon Peter Farrell
Peter Farrell
Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
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Table of Contents (14) Chapters Close

Preface
1. Fundamentals of Python 2. Python's Main Tools for Statistics FREE CHAPTER 3. Python's Statistical Toolbox 4. Functions and Algebra with Python 5. More Mathematics with Python 6. Matrices and Markov Chains with Python 7. Doing Basic Statistics with Python 8. Foundational Probability Concepts and Their Applications 9. Intermediate Statistics with Python 10. Foundational Calculus with Python 11. More Calculus with Python 12. Intermediate Calculus with Python Appendix

Discrete Random Variables

In this section, we'll continue learning about and working with random variables. We will study a particular type of random variable: discrete random variables. These types of variables arise in every kind of applied domain, such as medicine, education, manufacturing, and so on, and therefore it is extremely useful to know how to work with them. We will learn about perhaps the most important, and certainly one of the most commonly occurring, discrete distributions: the binomial distribution.

Defining Discrete Random Variables

Discrete random variables are those that can take only a specific number of values (technically, a countable number of values). Often, the values they can take are specific integer values, although this is not necessary. For instance, if a random variable can take the set of values {1.25, 3.75, 9.15}, it would also be considered a discrete random variable. The two random variables we introduced in the previous section are examples...

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