4 Ways to Measure Fat Tails with Python (+ Example Code)
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This is the 3rd video in a series about Power Laws and Fat Tails. In this video, I break down 4 ways we can quantify fat tails and share Python code analyzing real-world data.
📹 Series Intro: • Pareto, Power Laws, and Fat Tails
📹 Previous video: • Detecting Power Laws in Real-world Data | ...
📰 Read more: https://medium.com/towards-data-scien...
💻 GitHub Repo: https://github.com/ShawhinT/YouTube-B...
References
[1] Scipy Kurtosis: https://docs.scipy.org/doc/scipy/refe...
[2] Scipy Moment: https://docs.scipy.org/doc/scipy/refe...
[3] arXiv:1802.05495 [stat.ME]
[4] https://en.wikipedia.org/wiki/Log-nor...
[5] Pham-Gia, T., & Hung, T. (2001). The mean and median absolute deviations. Mathematical and Computer Modelling, 34(7–8), 921–936. https://doi.org/10.1016/S0895-7177(01...
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Homepage: https://shawhintalebi.com/
Intro - 0:00
Fat Tails - 0:45
4 Ways to Quantify Fat Tails - 2:02
Heuristic 1: Power Law Tail Index - 2:32
Heuristic 2: Kurtosis - 3:50
Heuristic 3: Log-normal's σ - 5:29
Heuristic 4: Taleb's κ - 7:04
Example Code: Quantifying Fat Tails in Social Media - 11:44
What's next? - 22:29
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