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Art Statistics How Learn Data
Published: March 12, 2026
Video Description
𝙎𝙄𝙂𝙉 𝙐𝙋 for tastefully infrequent updates about our upcoming Probability & Statistics course.
💌 https://snu.socratica.com/probability-statistics-course
Coins, dice, and even random integers all have something in common: a set of distinct outcomes you can list. That’s the world of discrete random variables.
Here we compare & contrast discrete and continuous random variables and learn the rules a discrete distribution must follow. We'll even see a surprising case where there are infinitely many outcomes but the distribution is still discrete!
▶️ 𝙒𝘼𝙏𝘾𝙃 𝙉𝙀𝙓𝙏:
Normal Distributions https://youtu.be/xlxaa9YhT6A
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𝘽𝙚𝙘𝙤𝙢𝙚 𝙤𝙪𝙧 𝙋𝙖𝙩𝙧𝙤𝙣 𝙤𝙣 𝙋𝙖𝙩𝙧𝙚𝙤𝙣:
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📚 𝙒𝙚 𝙧𝙚𝙘𝙤𝙢𝙢𝙚𝙣𝙙 (affiliate links):
The Drunkard's Walk: How Randomness Rules Our Lives by Leonard Mlodinow
https://amzn.to/4j9n0YP
The Art of Statistics: How to Learn from Data by David Spiegelhalter
https://amzn.to/3S9E46a
How to Be a Great Student (from Socratica!)
ebook: https://amzn.to/2Lh3XSP
paperback: https://amzn.to/3t5jeH3
🎬 𝘾𝙍𝙀𝘿𝙄𝙏𝙎:
Written & Produced by: Michael Harrison & Kimberly Hatch Harrison
Edited by: Alivia Brown and Megi Shuke
Music License from Soundstripe
Code: MSWKCNZ1WFQTCX2S
🎓 𝘼𝘽𝙊𝙐𝙏 𝙊𝙐𝙍 𝙄𝙉𝙎𝙏𝙍𝙐𝘾𝙏𝙊𝙍𝙎:
Michael earned his BS in Math from Caltech, and did his graduate work in Math at UC Berkeley and University of Washington, specializing in Number Theory. A self-taught programmer, Michael taught both Math and Computer Programming at the college level. He applied this knowledge as a financial analyst (quant) and as a programmer at Google.
Kimberly earned her BS in Biology and another BS in English at Caltech. She did her graduate work in Molecular Biology at Princeton, specializing in Immunology and Neurobiology. Kimberly spent 16+ years as a research scientist and a dozen years as a biology and chemistry instructor.
Michael and Kimberly Harrison co-founded Socratica.
Their mission? To create the education of the future.
Ready to 🧠 𝙇𝙀𝘼𝙍𝙉 𝙈𝙊𝙍𝙀 with Socratica?
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#probability #DiscreteDistributions #randomvariables