Bayes' Theorem EXPLAINED with Examples

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  • Опубліковано 2 кві 2023
  • Learn how to solve any Bayes' Theorem problem. This tutorial first explains the concept behind Bayes' Theorem, where the equation comes from, and finally how to use the formula in an example. Bayes' Theorem is one of the most common equations covered in Statistics due to its numerous applications to the real world. It is also one of the most misunderstood theorems, but this video will help clear all of that up!
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КОМЕНТАРІ • 172

  • @MohamedIsmail-fk9dd
    @MohamedIsmail-fk9dd Рік тому +192

    I don't know how this is not the most viewed Bayes' theorem video because its the most helpful in youtube

    • @AceTutors1
      @AceTutors1  Рік тому +16

      That means so so much to me! Thank you for saying that! I appreciate it!

    • @vikasyadav9345
      @vikasyadav9345 10 місяців тому +1

      I am Indian I have no words for saying video but I say few word this is very amazing and very helpfull in all students

    • @QbeamS
      @QbeamS 8 місяців тому

      Indeed, great vid. I also found this one to be very useful:
      ua-cam.com/video/1QulO1jS2Hk/v-deo.htmlfeature=shared

    • @ebrahimalabadi3328
      @ebrahimalabadi3328 3 місяці тому

      I totally agree

    • @Lunatic_Retz
      @Lunatic_Retz 3 місяці тому

      because it's not

  • @jsegor
    @jsegor Місяць тому +1

    Probably the clearest explanation of Bayes Theorem I have seen so far. Beautifully done. Got to watch all your videos now.

  • @allemagallied4775
    @allemagallied4775 10 місяців тому +6

    Thanks a lot for this intuitive example. It helped me a lot to understand this mechanism when I understood that as p(cloudy) becomes smaller, p(rain|cloudy) becomes greater, all else being equal. Since p(cloudy) is the numerator.
    This makes sense intuitively, because in a situation clouds are rare (i.e. p(cloudy) is smaller), but when it rains, there were often clouds in the morning (i.e. p(cloudy|rain) is large), the prediction value of it being cloudy in the morning is high.
    Reversely, in a climate where it is always cloudy (i.e. p(cloudy) is near one), the fact that it's cloudy in the morning does not tell you much in terms of how much rain you will get.

  • @bondoasanidze9169
    @bondoasanidze9169 2 місяці тому +4

    The best explanation of Bayes' theorem on youtube, thank you

  • @thelambsauce2015
    @thelambsauce2015 2 місяці тому

    Saying this video is the best is an understatement. Thank you so much for posting this beyond-amazing video!

  • @suirvival3120
    @suirvival3120 5 місяців тому +2

    Please make more videos on the probabilities. Thank you so much We appreciate your effort.

  • @MrNitinnavin
    @MrNitinnavin 9 місяців тому

    superb video. How easily the theorem is explained with the help an excellent example...thanks.

  • @carlossantos6683
    @carlossantos6683 Місяць тому

    That was easy and simple to understand. Master it is another thing, but my guess is that you saved me some precious time with this video. Thank you a lot.

  • @saikatsen391
    @saikatsen391 3 місяці тому

    Very precisely explained.Thank you Sir❤

  • @ogakjayoke6895
    @ogakjayoke6895 5 місяців тому

    Thanks for your videos. It helped a lot. Please do something on hypothesis. Thanks

  • @Sal-uh4dw
    @Sal-uh4dw 4 місяці тому

    This was very helpful am taking statistics class and was so lost. Thanks

  • @ogunyebigbemi1061
    @ogunyebigbemi1061 11 місяців тому +6

    This is so beautiful.
    I didn't understand it really at first, but after now I have a pretty great idea of it

    • @AceTutors1
      @AceTutors1  3 місяці тому

      That's terrific to hear! That is exactly my goal with my videos!

  • @soundharyasfeed7374
    @soundharyasfeed7374 4 місяці тому

    This was super helpful thank you!

  • @kamleshbaviskar8777
    @kamleshbaviskar8777 11 місяців тому

    Thanks! Very helpfull and understandable.

  • @lerevenger000
    @lerevenger000 Рік тому +12

    Please keep making more videos. I am an MPH student at Harvard, and you make the concepts extremely understable. Sending you a lot of love

    • @AceTutors1
      @AceTutors1  Рік тому +2

      Thank you so much for your kind words! I really appreciate it and will keep work on putting out videos.

    • @lerevenger000
      @lerevenger000 Рік тому

      @@AceTutors1 we need probability testing statistics if possible

  • @m3sam
    @m3sam Місяць тому

    I think the example in this video is better than what 3B1B gave in his Bayes' theorem video. The starting wasn't good because you just spammed the formula but the example and the way you conveyed it is really good. One can understand the principle through your example. Good work!

  • @cyberwolf575
    @cyberwolf575 2 місяці тому

    Amazing video, thank you for the explanation it finally clicked.

  • @user-wk3bt8ll9o
    @user-wk3bt8ll9o 5 місяців тому

    Thank you so much for this vid man, your method of explanation was impressive

  • @davidrogerdat
    @davidrogerdat Рік тому +28

    Great videos Mark, you inspire us every day with your slogan "You've big dreams, don't let a class get in your way."
    The likelihood of it being rain while picnic seems low, as it's less than 0.5 / 50%. So I think.i would still go on the picnic.

    • @AceTutors1
      @AceTutors1  Рік тому +1

      Thank you so much for your kind words and support! Ahh, you might have a higher risk tolerance than me! haha :)

  • @iradukundacynthiaamal
    @iradukundacynthiaamal Рік тому +2

    Thank you soo much for well explaining this concept. I now can say that I understand it better!

    • @AceTutors1
      @AceTutors1  3 місяці тому

      That's amazing to hear! Thanks for watching!

  • @minimin-wj8vp
    @minimin-wj8vp 4 місяці тому

    Super helpful ,Thank you 🌹

  • @TwoStepsTogether
    @TwoStepsTogether 8 днів тому

    Thank you so much. It took 1 video of you understand 3 hours of lecture.

  • @John14vs6_
    @John14vs6_ 2 місяці тому

    God bless you sir for this video. I HAVE went through few videos on UA-cam and this was one of the best where my mind has understood this fully. Now lets see if you have stuff on Binomial distribution. Thanks just subscribed now

  • @user-memefulreality3
    @user-memefulreality3 10 місяців тому

    Great explaination sir

  • @muhammedlaminceesay7881
    @muhammedlaminceesay7881 5 місяців тому

    honestly u did better job than many others

  • @Annes81-ro5xt
    @Annes81-ro5xt 9 місяців тому

    Super explanation. Thanks Sir

  • @zianiera
    @zianiera Місяць тому

    Good explanation.Thank you

  • @hamsterman1571
    @hamsterman1571 Рік тому +2

    love your work man, keep up the good work!

    • @AceTutors1
      @AceTutors1  Рік тому

      Thank you so much for the support!

  • @medaphysicsrepository2639
    @medaphysicsrepository2639 9 місяців тому

    this was great thnx for the example

  • @ChilledPudding
    @ChilledPudding 3 місяці тому +3

    THANKS MAN! Tomorrow is my official school graduation exam and honestly i didn't ecen know a word about this concept so i was worried and your video popped up! Thanks a bunch for making me understand it! Ill be back to report my marks if i am reminded of this comment!
    P. S: keep doing this. We love it and will support you through the best of our efforts!

    • @AceTutors1
      @AceTutors1  3 місяці тому +1

      Thank you so much for your comment! It's stories like yours that give me the fuel to make these videos. I wish you luck on your exam! And thank you for the support!

  • @chris-vr5pm
    @chris-vr5pm 6 місяців тому +3

    Got an exam in 8 min, this was good help

  • @successfulvictorypublisher6090
    @successfulvictorypublisher6090 5 місяців тому

    Thank you so very much!

  • @samarehab9029
    @samarehab9029 10 місяців тому +1

    Super helpful and straightforward. Thank you sir please keep posting

  • @jeonsanya
    @jeonsanya Рік тому +1

    Omg thank you sir thank you so much ❤ the way u explained it,, cleared my all doubts regarding this topic ❤

    • @AceTutors1
      @AceTutors1  Рік тому +1

      That's really awesome to hear! Thanks for the kind words!

  • @tuson1258
    @tuson1258 11 місяців тому

    This is very helpful❤

  • @beccajamae
    @beccajamae 3 місяці тому

    THANK YOU!
    I was trying to learn Bayes' Theorem off the example of "Go For Broke" the gameshow. 🥵 my brain was twisting in on itself. THIS I can understand.

  • @danielrasmussen4862
    @danielrasmussen4862 4 місяці тому

    English is not my first language and you still made it very easy :D

  • @ashimasingh9906
    @ashimasingh9906 8 днів тому

    Thanks for the concept ☺️ I think I will try to reschedule 😅❤

  • @MariaKaandje-ss7qv
    @MariaKaandje-ss7qv 22 дні тому

    great, great and best explanation

  • @fahad_hassan_92
    @fahad_hassan_92 Рік тому +2

    Great videos man they help a lot

    • @AceTutors1
      @AceTutors1  Рік тому +1

      Thank you so much! I appreciate it!

  • @TheSdlocal
    @TheSdlocal Рік тому +2

    I’ve never seen a more clear explanation of how Bayes’ Theorem can be applied. This is extremely helpful! Thank you so much!

    • @AceTutors1
      @AceTutors1  3 місяці тому

      Thank you so much for saying that! I really appreciate the support!

  • @deepsaliya9410
    @deepsaliya9410 9 місяців тому

    Great video thanks

  • @kashishjaveri
    @kashishjaveri 9 місяців тому

    Amazing video!! thank you:))

  • @purv_vlogs
    @purv_vlogs 5 місяців тому

    Good explanation 🎉

  • @mandelbrot3162
    @mandelbrot3162 9 місяців тому +2

    This series is amazing. Must have been hard to make these beautiful animations. Thank you so much❤.
    Can you please make two more distributions viz:
    1. "Poisson Distribution" and
    2. "Exponential Distribution"
    And explain the intuition behind the mean and standard deviation in these distributions like you did in Uniform distribution video?

  • @ferieldi8137
    @ferieldi8137 Рік тому +1

    It indeed helped ! appreciate it gentleman

    • @AceTutors1
      @AceTutors1  Рік тому

      Great, I'm so glad! Thanks for your support!

  • @alyaqistina597
    @alyaqistina597 6 місяців тому

    this helped tonnnnnnn thankyou

  • @studynow3540
    @studynow3540 6 місяців тому

    Thank you so much

  • @The_Right_One1
    @The_Right_One1 Місяць тому +2

    Which software are you using to make these videos?

  • @harshitgautam4098
    @harshitgautam4098 11 місяців тому

    Pretty helpful!

  • @TheSonicSegaNerd
    @TheSonicSegaNerd 23 дні тому

    Thank you for creating this theorem, Bae 😍

  • @user-mz6rr3qp7o
    @user-mz6rr3qp7o 4 місяці тому

    Thank you!

  • @user-ug6ju6gd6u
    @user-ug6ju6gd6u 3 години тому

    Thank you NRI ❤

  • @pinkywolfgaming1006
    @pinkywolfgaming1006 2 місяці тому +4

    i feel like i want to cry

  • @georgemouzakis8996
    @georgemouzakis8996 29 днів тому

    Thank you. I'm still having concept issues. As a teaching technique is it possible for you to summarize the meaning of the numerator and what the denominator accomplishes in the equation

  • @rspvsanjaykumargupta
    @rspvsanjaykumargupta 9 місяців тому +1

    How you will connect prior and posterior terms with this?

  • @CelestialWhisper464
    @CelestialWhisper464 10 місяців тому

    Damn, perfectly explained. Thanksssssssssss!

  • @prilveshkrishna3952
    @prilveshkrishna3952 Рік тому +2

    So farthis is the best bayes explanation. Can you explain this thing using a venn diagram and a probability distribution for the cloudy rain example

    • @AceTutors1
      @AceTutors1  Рік тому

      Thanks so much for your kind words! I'm not sure a probability distribution would help much, but some more Venn diagrams could be helpful! We'll consider this in a follow-up video! Thanks for the feedback!

  • @PK-qv5kv
    @PK-qv5kv Рік тому +1

    that was so helpful, thanks

    • @AceTutors1
      @AceTutors1  Рік тому

      You got it! Thanks for watching!

  • @risadwiratnasari748
    @risadwiratnasari748 9 місяців тому

    hi I want to ask so in this case what the addictional knowledge? the probability of beibg cloud?

  • @UKINFLUENCERS..2881
    @UKINFLUENCERS..2881 5 місяців тому

    Hi, so is conditional probability used with limited information in a question, however Bayes theorem can be used to answer a question that has more information? I'm just struggling with which one to use in an exam question

  • @infernodragon627
    @infernodragon627 6 місяців тому

    What an example ❤❤

  • @biguglypig5502
    @biguglypig5502 5 місяців тому

    great vids bro

  • @mohamedelkholy2421
    @mohamedelkholy2421 5 місяців тому

    Excellent

  • @nicksulistio569
    @nicksulistio569 7 місяців тому

    Thankyou!

  • @basantdipika
    @basantdipika 9 місяців тому

    Nice explain dear

  • @theeraphatsunthornwit6266
    @theeraphatsunthornwit6266 11 місяців тому

    Wow fairly good explanation. i just understand it perfectly today. However, in the process, i found another better way to comprehend this theorem.
    To those who still do not understand. Read this.
    First you must understand what p(a/b) is. It is the probability that a happening when we already know that b happened.
    To find p(a/b) we need to find prob that a and b happening at the same time , and divided it by prob of b happening.
    To find prob that and b happening at the same time (p (a interect b)), you can find that indirectly from prob that b happening when we already know that a happened multiplied by prob of a happening
    Ah.... i need a pen and a paper to convey this concept 🙄

  • @pardhatejakalla1974
    @pardhatejakalla1974 5 місяців тому

    Can we solve the same example by conditional probability?

  • @rafaelrodriguesdesiqueira4040
    @rafaelrodriguesdesiqueira4040 6 місяців тому +2

    it would make me 48% worried about rain and 48% considerable of postponing the picnic

  • @sidhartsatapathy1863
    @sidhartsatapathy1863 Місяць тому

    Do you use the Python library called "manim" to create these beautiful animations for your great videos.

  • @thienyetan2035
    @thienyetan2035 12 днів тому

    I would have liked if you incorporated dark clouds vs white clouds in the calculation.

  • @Creative_learning_with_Sajib
    @Creative_learning_with_Sajib 3 місяці тому

    nice example

  • @zafadoodle
    @zafadoodle 6 місяців тому

    I LOVE YOU GUYS

  • @kavyakavi2545
    @kavyakavi2545 3 місяці тому

    It's awesome 🎉😢

  • @lerevenger000
    @lerevenger000 Рік тому +1

    Can we please have a video about P value and what does it mean?? pretty please

    • @AceTutors1
      @AceTutors1  3 місяці тому

      Yes we have some videos on p-value in the works! Great idea!

  • @AbdShGazi
    @AbdShGazi 7 місяців тому

    Genius!

  • @TheFulger321
    @TheFulger321 4 місяці тому

    in need more explanation of this "give" thing

  • @sannibesh
    @sannibesh 2 місяці тому

    I am from Bangladesh, have started to learn machine learning. For which I have to learn probability and statistics.
    I have clear out all the topics on probability by 11-12th books. But BAYES' THEOREM was seemed to tough to understand.
    So I came to UA-cam and saw lots of videos which was even approximately half an hour! Although they tried for a long time, they all were gloomy to understand.
    But your 8 minute video is so effective than all those videos. Thanks. I have subscribed your channel. I will visit again if any other topics I have to understand in future.

  • @Siddu-ff6iv
    @Siddu-ff6iv Місяць тому

    you really aced it

  • @therice8024
    @therice8024 Рік тому +1

    Ive seen bayes theorem be written as P(Ei|A) = P(Ei)P(A|Ei) / ∑ P(Ek)P(A|Ek)
    can you explain this version?

    • @AceTutors1
      @AceTutors1  Рік тому +1

      Great point! This version is a more general formula if there are more than 2 events being considered. In this video, we just used the simplified version of 2 events to make it easier.

  • @ebrahimamin453
    @ebrahimamin453 7 місяців тому

    NICE VIDEO

  • @quynhd.2334
    @quynhd.2334 5 місяців тому

    I think the most difficult part overall regarding to probability problems... are the wordings. They seem to be confusing

  • @Glitch777
    @Glitch777 8 місяців тому

    Thus is amazing

  • @taiahking1226
    @taiahking1226 9 місяців тому

    That's great when the example gives what P A|B is

  • @ComercioExteriorUV
    @ComercioExteriorUV Рік тому +1

    Nice!

  • @rocco3935
    @rocco3935 Місяць тому

    if one knows that there are 12 rainy cloudy days (the 80% of 15) in 100 days and 25 cloudy days in total why one can’t just calculate 12/25= 0.48, without all the machinery and the language that the Bayes formula brings along? Is there something wrong in just applying the definition of probability?

  • @Brian-zj4mm
    @Brian-zj4mm 6 місяців тому

    Depends on how much you like picnics, how often you want to go on picnics, if you think rain ruins it and maybe you might already think a cloudy day isn't nice for picnics.
    But before we think about that, let's think about the ethics of holding a picnic and it's core components. We NEED to apply divide and conqure on this problem before we could even start to make a decision.
    We might even need to apply derivatives to calculate the slope at how long the picnic takes (x) and how much fun it is (y). Then we can decide the optimal time to hold the picnic 🙊

  • @ernstvankleij5978
    @ernstvankleij5978 Місяць тому +1

    I'm still puzzeld on which data is A and which is B - and why. Swapping things around changes the outcome of the formula, doesn't it?

  • @ahmedhesham2474
    @ahmedhesham2474 2 місяці тому

    thankkkkkkkkkkkk youuuuuuuuuuuuuuu !

  • @atahanbulut7445
    @atahanbulut7445 2 місяці тому +1

    Dude, when the guy says hit the subscribe button, the button lights up. I noticed it just now

  • @bellaruiz8991
    @bellaruiz8991 4 місяці тому

    You explain very well but it would be more helpful if you broke down how to determine step by step which is a and which is B.

  • @pawelpap9
    @pawelpap9 3 місяці тому

    On the last slide with example it should be “when it rains”, not where.

  • @thefantasticman
    @thefantasticman Рік тому +1

    CAN YOU EXPAIN THE TIME SERIES

    • @AceTutors1
      @AceTutors1  Рік тому

      That's definitely a topic we plan to cover in the future! Thanks for the feedback!

  • @aabi.4286
    @aabi.4286 2 місяці тому

    How did you made your subscribe button glow at 0:25 ??

  • @user-qy9rb3gb7d
    @user-qy9rb3gb7d 4 місяці тому +1

    legend

  • @libandahir7953
    @libandahir7953 10 місяців тому

    Definitely reschedule the picnic

  • @user-ls3bi6jk8u
    @user-ls3bi6jk8u 11 місяців тому

    It is observed that 76% of Group A favors the product, 47 % of Group B favors the
    product and 54% of Group C favors the product. A random sample of 105 people
    with 35 from group A, 28 from Group B and 42 from Group C, was chosen and
    polled. A random vote from the poll suggests that the product is preferred. What is
    the probability that this vote belongs to a person from group B? Can anyone tell me the answer for this?

    • @rose-iu5ij
      @rose-iu5ij 6 місяців тому

      20.17% or 47/233

  • @cemcanbolat8968
    @cemcanbolat8968 5 місяців тому +1

    I think this solution is incorrect actually. We should have calculated P(C) with the rainy days' 0.85 ratio with the formula : P(C)=P(C∣R)×P(R)+P(C∣¬R)×P(¬R) where C is being cloudy and R is rainy. So it would be 0.12 for P(C∣R)×P(R) and 0.215 for P(C∣¬R)×P(¬R) and the calculations made it's 0.36. Can you clarify please

  • @trainingbrah4018
    @trainingbrah4018 2 місяці тому

    So what you’re saying (if I pause the video @6:23) is:
    If the probability of it being cloudy outside is 4 times greater if it also rains that day, then the probability of it raining on any given day is also 4 times greater if it happens to be a cloudy day?

    • @trainingbrah4018
      @trainingbrah4018 2 місяці тому

      I essentially just pretended that P(cloudy) was equal to 0.2 instead of 0.25, and then I just isolated the ratio of: P(cloudy/rain)/P(cloudy)

    • @trainingbrah4018
      @trainingbrah4018 2 місяці тому

      Given the statement "it’s 4 times more likely to be cloudy outside, given it is also raining," we can express this as:
      P(Cloudy | Rain) = 4 * P(Cloudy)
      Substituting this into the Bayes' theorem equation, we get:
      P(Rain | Cloudy) = (4 * P(Cloudy) * P(Rain)) / P(Cloudy)
      The P(Cloudy) term cancels out, resulting in:
      P(Rain | Cloudy) = 4 * P(Rain)
      So, yes, from a simple Bayesian probability standpoint, if it's 4 times more likely to be cloudy outside given that it's raining, then it's 4 times more likely to rain given that it's cloudy outside.

  • @saintrhemajl
    @saintrhemajl Рік тому +2

    We humans do fear water than anything

    • @AceTutors1
      @AceTutors1  3 місяці тому

      Nobody likes a rainy picnic!