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Essential Statistics for Non-STEM Data Analysts

You're reading from   Essential Statistics for Non-STEM Data Analysts Get to grips with the statistics and math knowledge needed to enter the world of data science with Python

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781838984847
Length 392 pages
Edition 1st Edition
Languages
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Author (1):
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Rongpeng Li Rongpeng Li
Author Profile Icon Rongpeng Li
Rongpeng Li
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Getting Started with Statistics for Data Science
2. Chapter 1: Fundamentals of Data Collection, Cleaning, and Preprocessing FREE CHAPTER 3. Chapter 2: Essential Statistics for Data Assessment 4. Chapter 3: Visualization with Statistical Graphs 5. Section 2: Essentials of Statistical Analysis
6. Chapter 4: Sampling and Inferential Statistics 7. Chapter 5: Common Probability Distributions 8. Chapter 6: Parametric Estimation 9. Chapter 7: Statistical Hypothesis Testing 10. Section 3: Statistics for Machine Learning
11. Chapter 8: Statistics for Regression 12. Chapter 9: Statistics for Classification 13. Chapter 10: Statistics for Tree-Based Methods 14. Chapter 11: Statistics for Ensemble Methods 15. Section 4: Appendix
16. Chapter 12: A Collection of Best Practices 17. Chapter 13: Exercises and Projects 18. Other Books You May Enjoy

Understanding the power law and black swan

In this last section, I want to give you a brief overview of the so-called power law and black swan events.

The ubiquitous power law

What is the power law? If you have two quantities such that one varies according to a power relationship of another, and independent of the initial sizes, then you have a power law relationship. Many distributions have a power law shape, rather than normal distributions: . The exponential distribution we saw previously is one such example.

For a real-word example, the frequency of words in most languages follows a power law. The English letter frequencies also roughly follow a power law. e appears the most often, with a frequency of 11%. The following graph taken from Wikipedia (https://en.wikipedia.org/wiki/Letter_frequency) shows a typical example of such a power law:

Figure 5.11 – Frequency of English letters

What's amazing about a power law is not only its universality...

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