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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

Introduction

In previous chapters, we have described and explored data using descriptive statistics and visual techniques. We have also looked at probability, randomness, and using simulations of random variables to solve problems. The idea of distributions was also examined, which plays a much bigger role later in this chapter.

When looking at applying statistical ideas, there are some important questions to answer concerning methodology. Some examples of these questions could include "how large should I make my sample?" or "how confident can we be in the results?". For this chapter, we will look at how we can apply two of the most important theorems in statistics, starting with their practical implications before moving onto solving common problems using the more useful techniques that are derived from these important ideas.

In this chapter, we will explain what the law of large numbers is and clarify how sample size affects the sample mean. The central...

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