But what is the Central Limit Theorem?

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Published 2023-03-14
A visual introduction to probability's most important theorem
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Galton board shown in the video: amzn.to/3ZJK8nY

Thanks to these viewers for their contributions to translations
Hebrew: David Bar-On, Omer Tuchfeld
Hindi: Tapender1
Italian: anna-lombardo

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Timestamps
0:00 - Introduction
1:53 - A simplified Galton Board
4:14 - The general idea
6:15 - Dice simulations
8:55 - The true distributions for sums
11:41 - Mean, variance, and standard deviation
15:54 - Unpacking the Gaussian formula
20:47 - The more elegant formulation
25:01 - A concrete example
27:10 - Sample means
28:10 - Underlying assumptions

Correction: 6:37 The narration should say "skewed left"
Correction: 7:15 Again, the narration should say "skews a tiny bit left"

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All Comments (21)
  • Please consider doing an entire series on probability theory and/or combinatorics.
  • @roncho
    I'm an engineering professor far more older than you and I must say whitout a doubt: you are the most skilled professor I have ever seen. The amount of work in this videos is outstandig. They are so flawless that can be considered as art. Congratulations!.
  • I have a PhD in applied mathematics, I work in numerical weather prediction as a research scientist. Gaussianity is this hardcore part of the basics of forecasting the weather (even though most atmospheric variables, and their errors, are actually non-Gaussian). This video did a great job at teaching the CLT. I have never seen it explained so well.
  • @stratfanstl
    The actual rigorous no-jokes-this-time conclusion from watching 3Blue1Brown videos like this is that Grant deserves some new, yet-to-be invented prize that should be the equivalent of an Oscar for best computer generated imagery, an Emmy for outstanding narration / editing and a Nobel Prize in science for fostering interest in mathematics and science. Amazing, inspired work here.
  • @JaGWiREE
    Of all the years I've supported 3b1b, this video might be the one I was most excited to see pop up.
  • @3blue1brown
    Next video, explaining the π and how the function e^(-x^2) arises: https://youtu.be/cy8r7WSuT1I As many helpful commenters have pointed out, at 6:37 and 7:15 the narration should say "skews left" instead of "right". In standard terminology, the skew direction refers to the direction of the longer tail.
  • the section unpacking the Gaussian formula is simply a work of art. Giving a graphical intuition about moving from e^(-x) to e^(-x^2), and then to a constant multiplier of the exponent... just absolutely pristine
  • @swanmath8382
    This series of lectures must be incorporated into the math curriculum of all high schools in the world, I was trained in math and as a data scientist, but I have never seen the central limit theorem explained this way. It just made things so easy to understand and intuitive. Well done.
  • @kev2582
    Dealing with CLT pretty much every day here. Really impressed with how easily you explain it. By far the most intuitive and easily understood explanation of CLT. Salute!
  • @robinj.p.7187
    Describing the mean of the weights as the center of mass of the distribution was just incredible. And the intuitive matrix multiplication without even mentioning it. You are a great teacher!
  • I can't tell you how insanely brilliant you are at taking a universal concept that is vaguely understood and illuminating all the nuance hidden in plain daylight to make this understood on a higher level!!! Genius
  • @scrimbingus
    As someone who works with Kalman filtering on a regular basis, this is a very nice video to see. One of the core principles behind the Kalman filter is that all random variables involved must be Gaussian, which seems overly restrictive on the surface. I think this provides an excellent, succinct explanation for why that's actually a reasonable assumption for many systems, since every random process we can directly observe is really just a combination of many smaller processes. I look forward to the next one!
  • @0x90meansnop8
    Grant, you are a lifesafer! My exams are in 2 weeks and I have not understood this yet. It's a miracle you are publishing this video online!
  • @mimid3312
    Thanks for producing such high-quality videos, i'm a maths student who love statistics. I would say this vid gives the clearest and neatest explanation to CLT ever, really inspiring, I sacrificed my sleep time watching it for 3 times!!! Amazed and shocked! Thank you Grant. <3
  • As I was watching this video, I wanted to say that videos from your channel inspire me to learn. Not just mathematics, but anything worth doing. Although I am an engineer and enjoy doing what I do, I have never been a huge fan of pure mathematics. But the way you explain concepts just makes it so easy to understand. Even though I might have to rewatch some videos to fully comprehend the meaning, I really enjoy it and it never feels like a chore. I have watched your videos more than my university lectures. I wish there are more teachers like you in this world. Thank you so much 3Blue1Brown!
  • @TonyLeTone
    This video is by far the best introduction to the CLT I've encountered. You are doing the world a great service by putting that much effort into this youtube channel. I adore your work and use your visualizations all the time in my classes (even though I teach in french).
  • I would absolutely love to see a series on probability/combinatorics/statistics on this channel. It's the subject I've struggled the most with in math by far. I think your ability to take the time to really think through and understand what the basic building blocks really mean will become a very valuable resource in my and many other people's math journeys.
  • @paulwilk2854
    I am constantly impressed by how Grant's videos extract the art that is inherent in certain mathematical concepts. What a great video!
  • @jordan6302
    As an actuary, I'd say this is perhaps the best descriptive video/lecture I've ever seen on the CLT. I wish I would have seen this when taking my classes for exam P because the visualizations are so useful in understanding what can be a very dense topic when it's spewed from a chalk board/overhead screen hastily.