Title | : | Bayes theorem, the geometry of changing beliefs |
Lasting | : | 15.11 |
Date of publication | : | |
Views | : | 3,6 jt |
|
When I read Kahneman and Taversky’s many years back, I found it very interesting, but I never thought it had much to do with probability (even though there are many probability examples), rather it’s about psychology and how people, or their presumed fast thinking brains, are very sensitive to the exact phrasing of the question, so much so that it doesn’t matter what the question actually is because they decide what the question ought to bebrbrIn the bank teller example, most people have decided that Linda is already known to be a bank teller, so the question is only whether she is also feminist or not Comment from : @aroundandround |
|
You say people are not expected to know this but you’d think given a context where it’s a natural question, people would guess that, after all, it makes sense that the thing we need more of has more people doing it Comment from : @S8EdgyVA |
|
I feel like its not necessarily even about the number of people, though thats an important point; farmers dont need to interact with people nearly so often, and do need to be tidy (planting in rows) Comment from : @chrstfer2452 |
|
Came across this video on a whim and I gotta say, I studied computer science in college with multiple classes touching on this subject and this is by far the best explanation I’ve ever seen Fantastic teaching Comment from : @FATMAN92769 |
|
People wouldn't consider the ratio of farmers to librarians when answering that question because it is irrelevant It was not stated, nor should be expected, that the person in question was plucked uniformly at random out of the US population They are simply given an example person, who in fact sounds like it was cherry-picked for the sake of the exercise Using the ratio of farmers to librarians in the population at large is flatly incorrect in this case Comment from : @isodoubIet |
|
you are gifted Grant! believe me! you changed my deep understanding of probability Thanks! Comment from : @armankhalifehsoltani4223 |
|
With this, I will never forget Bayes Theorem! Thanks a lot man! Cheers Comment from : @JM-ko8qz |
|
Thank you so much! Comment from : @fallingstones2396 |
|
well i think alltought 1 farmer can feed 1 million libartians i think steve is a hunter since their are allreadey enought libarians Comment from : @ulyssesk7325 |
|
Man, you have the best Mathematics youtube channel in the world and evidently, you are the best mathematics tutor Comment from : @user-jm2cp3oq4r |
|
Given the description it is still more likely that Linda is both a bank teller and active in the feminist movement than that she is merely a bank teller, mainly due to the key phrase "social justice" Comment from : @MotesTV |
|
I'm so thrilled and grateful to have you as my math teacher Beautiful era to live in! Comment from : @kingshukcs |
|
ideal Comment from : @forthefuture2273 |
|
LET'S GO! Comment from : @pietromicelli11 |
|
i think the introductory example is disingenuous When people ask a question like that "here is a description of a person is he class A og B", it is not appropriate at all to assume this is person is randomly sampled from the population i think what is instead implied, the way most people hear such a question, is that the person is sampled from the archetypes of their respective classes Eg you take the x most libererian libererians and x most farmer farmers, and pick one why would you say its eigther a farmer or a liberarian if not Is a more valid answer that you think hes a teacher because those are more common?brbrnow i would say as an example to teach bayes theorem, this is not that bad However many people will use such thought experiments to try to convince people to use a more "logical" mindset The fact is in the real world when you are faced with a question like that, not asked by someone that designed it to trick you, cleansing your mindset from context, and trying to find a few variables and use math will be less accurate than using your intuition on the whole context of the question asked, why it was asked, who asked, etc Comment from : @codelapiz |
|
im not gonna lie this video pisses me off Comment from : @38zech |
|
im not gonna lie this video pisses me off Comment from : @38zech |
|
I shall honour your channel in my inauguration Thank you Comment from : @abexoxo |
|
@3blue1brown could you also make a brief video on MAP and MLE Lot of love and respect for your work Comment from : @Dutta1605 |
|
Watching this video again, I have to say, it's brilliant Comment from : @e11e7en |
|
whenever I saw classic probability problem of positive negative test result, I used to think bayes theorem is absurd as its telling the probability of having disease is lower even though the result is +ve But after watching this video, everything makes sense Much Thanks for this video :) Comment from : @ashithen1833 |
|
What seems to bother/confuse me is that bayse theorem just looks like a static equation about joint probability It seems to just describe a static reality But the interpretation is a dynamical/iterative scheme to update subjective belief brbrThe libertarian-farmer example has a hypothesis that has a well defined prior probability (the fraction of librarian is a objective reality) In other context, the probability about belief is fundamentally ill defined For instance, the likelihood of string theory is correct (over all current theory) has a definite binary answer while our assignment of prior probability is totally ill defined and subjective This example is more about updating subjective belief while the librarian-farmer example is more about describing well defined static reality One example requires some kind of iterative convergence to give rigorous result while the other give rigorous result without the need for iteration Comment from : @bohanxu6125 |
|
If 3b1b was everyones math teacher,humanity would be hundreds of year ahead in terms of techonology Comment from : @necastavasbriga5989 |
|
bruhh I dont get it Comment from : @dweeder1453 |
|
Very well explained, congratulations!!! I would like to ask if on the minute 4:20 there should be 40 instead of 4? Comment from : @AIEasySolutions |
|
as a statistics major this is so beautifully done, the intuitive understanding of probability takes years to achieve, yet you managed to beautifully present it in a video, congrats ❤️ Comment from : @michacuylits7254 |
|
🎯 Key Takeaways for quick navigation:brbr00:00 🧠 bEntendiendo el objetivo del Teorema de Bayes/bbr- El objetivo del Teorema de Bayes es comprender cómo la nueva evidencia debe actualizar creencias previasbr- Se plantea el caso de Steve y cómo nuestras percepciones iniciales pueden no considerar la información relevantebr- Bayes ofrece una fórmula para actualizar creencias basadas en evidencia, no para determinarlas completamentebr04:52 📊 bComprendiendo Bayes’ Theorem: Fórmula y aplicabilidad/bbr- Bayes’ Theorem calcula la probabilidad de una hipótesis después de observar evidenciabr- La fórmula de Bayes implica la probabilidad previa, la verosimilitud y la probabilidad de la evidenciabr- Aplicaciones de Bayes en ciencia, inteligencia artificial y en cómo modelamos nuestras propias creenciasbr08:54 🤔 bAmpliando la intuición sobre la probabilidad más allá del Teorema de Bayes/bbr- La importancia de representar mentalmente muestras representativas para comprender mejor la probabilidadbr- Ejemplo de Kahneman y Tversky sobre cómo la presentación de la información afecta nuestras percepcionesbr- Probabilidad vista como proporciones y la utilidad de la geometría en la comprensión de Bayes' TheorembrbrMade with HARPA AI Comment from : @Cuansf |
|
It is the best video I have ever watched about Bayes theorem! I am also looking forward to tutorials about making the video I really like this style! Comment from : @yijingwang7308 |
|
Bayes theorem is good - in my mind it is a way of quantifying being 'holistically thorough' or 'sherlocking' it I think there may be value in finding a more widely applicable opening example Comment from : @autumnthriller |
|
I think I know too many librarians for the example to work on me the way it was supposed to, in particular the "shy and withdrawn with very little interest in people" part made it not feel particularly more suited to being a librarian, which is a job that in fact requires a LOT of public interaction Comment from : @HunterJE |
|
I think of it as "probability of a true positive divided by the sum of the probability of a true positive and a false positive" Comment from : @KCObamacan |
|
Proportion is the word! Thinking about probability in terms of proportions just makes it so comprehensible and easy Comment from : @avimandavia6154 |
|
The best way to approach any problem is to break it down into simpler problems , look for patters and possible manipulationsbrbrBut how to do that?😂brI am able to break it down , I am able to identify patterns (sometimes not) but the part of doing serious and out of the box manipulation, I am not able to do it Teach me😊 Comment from : @theinterpreter3705 |
|
Thanks! Comment from : @realdealbasile |
|
thank you so much i finally got the point thank you thank you thank you Comment from : @xxxx3732 |
|
I just want to say, thank you for this point of view Comment from : @mirovskii |
|
Can't Thank you enough for the illustrations that make everything clear and easy to recall Also, the fact that it is not just about teaching the formula but the concept and the notion of it is what we all need Thanks a million Comment from : @alaaseada4659 |
|
I need to repeat watching this 100 times Comment from : @macaion897 |
|
THANK YOU this video is very very very didactic and easy to understand Your channel is amazing!!! Comment from : @GabriellaVLara |
|
Hii, I am steve Comment from : @dhruvilpatel4218 |
|
The statement evidence should not determine belief but only update your prior beliefs also cannot be taken as an absolute It is contingent on the evidence and the nature of the belief under consideration, isn't it? Comment from : @surajv1986 |
|
amazing video thank you so much!!!! Comment from : @antonisstellas741 |
|
I found that the parts “has a need for order and structure” and “passion for detail” to be the traits more becoming a librarian Comment from : @NightnessDev |
|
What would be a number value to "It's easier to get somebody to believe a lie than to get them to believe that they have been fooled by a lie"? Is there a friction coefficient? Comment from : @GeoScorpion |
|
I really enjoy watching your videos Thank you for expanding knowledge in such a beautiful way ❤ Comment from : @armandavari5556 |
|
"Rationality is not about knowing facts, it's about recognizing which facts are relevant" brbrThat sounds like a quote, is it? If so, what's the source, I'd like to quote it" Comment from : @stevenowens4511 |
|
Man I love you! Comment from : @user-mp2ct6qy2w |
|
The question does not give any indication, not even a vague one, of Steve being a random pick from a population Hence to make that assumption would be illogical, and have a low probability of being true Comment from : @simont6439 |
|
This is the worst explanation i have ever seen Time to see some indian guy explain this as straight forward as can be Comment from : @mahedihassanrafin7493 |
|
Just for the sake of trying to understand the problem with Linda, I think it might be useful to consider 2 things: 1 Saying either she is a bank teller or a bank teller and an active feminist, I think, makes people conclude the "bank teller" answer means "she is bonly/b a bank teller" as in, she is specifically bnot/b participating in feminism in any way (some might even extra erroneously think the question is asking whether or not she is for or against feminism), which her bio seems to contradict 2, I mean her description is so close to saying "I am a passionate feminist" that ignoring that when answering the question seems almost insanebrbrI guess what I'm saying is I would argue the bstudy/b is inherently flawed, and not the conclusions people are coming to when answering that The first issue, farmer vs librarian, on the other hand, does not have this problem So those results are probably much closer to the truth Comment from : @kittenbouquet |
|
Also funny because that description is almost as applicable to farmers as to librarians Comment from : @danielmagee8637 |
|
Great for understanding Bayes' theorem, but that paper's questions are obviously useless - the Linda question is an XOR, Comment from : @ChristopherBradfield |
|
Dude, you are a magician your videos have opened up this new world for me, which was so unapproachable to earlier, so beautiful Thank you so much for these videos Comment from : @pratikpatil87 |
|
Finally a clear explanation of Bayes Theorem that's easy to understand, thank you! Comment from : @AndrewCatanach |
|
Genius!! Thank you so much Comment from : @marianavillabona2022 |
|
The PIs are very cute Comment from : @Fjodorz |
|
Comment from : @oofsper |
|
Genius Comment from : @alamey4442 |
|
Thanks! Comment from : @shiluo4728 |
|
Amazing video! The illustrations are really useful! Comment from : @flaviopibetagama |
|
Love it!!! Comment from : @Carol-ppp3189 |
|
I was so confused in this topic U really explained this so easily Thank you!!! Comment from : @studlee |
|
I am very thankful to you for this explanation Comment from : @wickedclamor4882 |
|
Nobody explained me bayes theorem in the way you did Won't forget it for life Thanks Grant Comment from : @ayanangshudasmajumder112 |
|
i think the appropriate answer to the farmer/librarian conundrum would be 'not enough information'brbrwith a little thought it's clear both a farmer and a librarian could possess the listed characteristics a more telling quality would be (eg) does he prefer to work outdoors in all kinds of weather or does he prefer to work inside a climate controlled environmentbrbrmy first thought would not be to wonder about the ratio of farmers to librarians in the general population tbh Comment from : @cinidude |
|
Thanks! Comment from : @nintendan |
|
Freddy cono e madre viva maduro Comment from : @eliastsoukatos2 |
|
Steve is an NPC Comment from : @AlvaroMartinGrande |
|
More vaccinated than the non-vaccinated in the hospital in a society where 90 of the people is vaccinated!! What a weird and suspicious phenomenon??? How can it be?? It's not an accident for sure! Comment from : @karoltrzeszczkowski9567 |
|
So basically we’re saying “out of the people that *are actually shy like Steve*, what is the proportion of them that are shy librarians already?” Because to claim Steve will be likely to a librarian due to his shyness, we need to have seen evidence that librarians tend to be shy in the first place Comment from : @randywa |
|
As a child of a library household growing up in the middle of a rural agicultural bubble, that "meek and tidy" bit was a lot to process! (In my time I have observed both farmers and librarians displaying a very wide range of behaviours!) Comment from : @greentape7817 |
|
I will get a tattoo of this formula on my arm Comment from : @sonnguyenhoang5024 |
|
LOL Comment from : @hdd_1230 |
|
Thank you my man Comment from : @hamedazimi2726 |
|
May anyone could tell me by which software can make this kind of video? Comment from : @planepaper4347 |
|
It is an excellent explanation, but as a few others have already indicated, you've made an error by equating verbal misunderstanding with cognitive fallacy Implicit to the listener in the first question is that the questioner is talking about a population of two people (one librarian and one farmer) rather than the population as a whole Kahneman is much more careful to define conditions in his version of the question (Tom W), but ultimately, makes the same mistake by not accepting that questions in human language depend a great deal on context and unspoken assumptions I am not saying that such cognitive fallacies are unreal; just that language is a slippery animal that can be hard to pin down Comment from : @squillomeister |
|
You explain Bayes theorem in under 7 minutes My lecturer could not do that in 90 minutes Btw I’m in a QS top 20 university Comment from : @lym3718 |
|
condition is a more appropriate term here than evidence meek is a criterion or condition, not evidence there are a total of 24 people who fit this condition! Comment from : @fa7234 |
|
aha its quite simple, Steve likely to be a farmer because he is a male bbig brain intensifies/b bhalf read thinking fast and slow falls out the bag/b Comment from : @leonhardeuler4292 |
|
"Rationality is not about knowing facts, it's about recognizing which facts are relevant" - I'm borrowing this line Fucking gold! Comment from : @krishnakumarsubramanian3292 |
|
0:35 "Multiple different levels of understanding" Bayes Theorem This means we need bayes theorem to understand Bayes Theorem??!! Comment from : @madhukrishnavallabhajosyul6996 |
|
That stereotype is created by Hollywood 😅 Comment from : @VinayakPattanashetti |
|
The whole problem arises from semantics of unspecified conditions in a questionbrDefault cultural standard is to compare average librarian with average farmer, so the answer is that it’s more likely that average librarian is shybrMeanwhile what you refer to as new evidence is data needed to resolve the question with added specified condition: accounting for population statistics, thus not avarage, but any given librarian or farmer insteadbrYou can not retrospectively state that the first (default) answer is false, because you would have to update the question as wellbrIncompleteness of original request does not invalidate the given answerbrIt’s like asking: what is the chance that one of twelve crayons has a lucky color?brProblem is ill defined, because lucky color is a subjective definition of condition, which can be interpreted in many ways: my lucky color, color which is considered lucky in my culture, our culture, any culture, etc Comment from : @tayablackrose29 |
|
Talk about a lightbulb moment! This is genius Of COURSE it's about proportions and therefore, geometry Thank you! Comment from : @johnhibble7637 |
|
I shared an analysis of Bayes Theorem and the Monte Hall problem with Steve Strogatz about 12 years ago, based on Byrne ;) Comment from : @rjbriggs547 |
|
I frequently share this video with LabLeak deniers to get them started on understanding that it's the only explanation worth considering at this point Comment from : @skenzyme81 |
|
My teacher who has an experience of 20 years recommended your channel bro great work dude Comment from : @vamsikrishna3315 |
|
That second question about Linda was used in a training seminar I went to for my job, and many people not only chose option 2, but continued to argue for it after it was explained Comment from : @Preserbius |
|
Reminds me of partial derivatives and chain rule, fascinating Comment from : @milespiano |
|
John grew up very interested in science He has a high IQ and is very adventurous brbrDoes John work at Amazon or is he an astronaut?brbrDid you say Amazon because it is statistically more likely? Cool That means details of a person’s life aren’t even relevant to such a question brbrThe question you should have asked is “what job is a person more likely to attain, astronaut or Amazon?” Comment from : @jordonlongley6576 |
|
god those two examples where so fucking bad and his response to people's "wrong" answers was even worse this is why statistics is only as useful as the person using it Comment from : @Atomic-Monkey |
|
thanks a ton @3blue1brown, you are changing the P(H/E) of good teaching/better worldbryou are one of those very few people who are changing the world for goodbrone concept and one video at a timebrcheers!! Comment from : @sas-ko1ve |
#39 Bayes Theorem - With Proof u0026 Example |ML| РѕС‚ : Trouble- Free Download Full Episodes | The Most Watched videos of all time |
Garena DDTank:Combo 2000 Tốc Độ Sẽ Kinh Khủng Như Thế Nào?Best Cướp Turn Cân Team Lật Kèo РѕС‚ : Review Game N.B.H Download Full Episodes | The Most Watched videos of all time |
How To Change Beliefs РѕС‚ : Gary van Warmerdam Download Full Episodes | The Most Watched videos of all time |
Reviewing Every Secret Coin in Geometry Dash РѕС‚ : GD Colon Download Full Episodes | The Most Watched videos of all time |
How to Make Less Annoying Gameplay in Geometry Dash РѕС‚ : GD Colon Download Full Episodes | The Most Watched videos of all time |
? +100 ALMOST FREE USER COINS ON GEOMETRY DASH [2023] РѕС‚ : Jogolate Download Full Episodes | The Most Watched videos of all time |
30 EASY USER COINS AND 20 FREE STARS! (2020) | Geometry Dash РѕС‚ : Galluxi Download Full Episodes | The Most Watched videos of all time |
MATH u0026 GEOMETRY Vocabulary and Terminology in English РѕС‚ : Adam’s English Lessons · engVid Download Full Episodes | The Most Watched videos of all time |
I Want Coin | "Mulpan Challenge #36" | Geometry dash 2.11 РѕС‚ : Mulpan Download Full Episodes | The Most Watched videos of all time |
ALL SHOP (Total 118) | Geometry Dash 2.11 ~ 2.2 РѕС‚ : Partition Zion Download Full Episodes | The Most Watched videos of all time |