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The Binomial and Poisson Distributions

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  • Опубликовано: 8 авг 2024
  • If on average, 3 people enter a store every hour, what is the probability that over the next hour, 5 people will enter the store? The answer lies in the Poisson distribution. In this video you'll learn this distribution, starting from a much simpler one, the Binomial distribution.
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Комментарии • 24

  • @xxelurraxx232
    @xxelurraxx232 Год назад +5

    Thank you SO much. Especially for deriving the formula. I kept reading about how the Poisson distribution was the limiting case of the Binomial distribution, but didn't understand what people meant until now. Your graphics are amazing. Thank you for sharing your knowledge and putting so much work into this!

  • @zelalem9249
    @zelalem9249 Год назад +3

    Very brilliantly described. You refreshed my Maths (that I did long time ago) very nicely. Thank you very much.

  • @prakashselvakumar5867
    @prakashselvakumar5867 Год назад

    Explained well! I understand that you have put lot of effort to make this video visually appealing and color coding. Thank you.

  • @shashankshekharsingh9336
    @shashankshekharsingh9336 9 месяцев назад +1

    amazing , never saw someone explaning like this , thanks you

  • @leonnomos1384
    @leonnomos1384 Год назад

    Excellent pedagogical approach! Clarified very much

  • @florentinosanchez3969
    @florentinosanchez3969 4 месяца назад

    Awesome explaining. Thank you so much for making this !!!!!❤

  • @piobr
    @piobr 4 месяца назад

    Absolutely high quality video! Thank you so much. ❤

  • @sassydesi7913
    @sassydesi7913 Год назад +1

    I came here based on Jay's shoutout in his Keynote video. And glad here. Your tuts are visually appealing. We'd love if you could give a quick walkthrough of how you got about using Keynote to make animations. Like your typical workflow and tips/tricks while using Keynote.

  • @simeonthomas5881
    @simeonthomas5881 Год назад

    Great video as usual! Please also explain Geometric, Exponential, Weibull, Erlang, NBD etc. Thanks!

  • @ja100o
    @ja100o Год назад +1

    Small improvement for the chapters: 11:08 is the start of the Poisson distribution.
    Other than that, great as always:)

  • @yingqu6932
    @yingqu6932 Год назад

    Never seen better, awesome A+

  • @samirelzein1095
    @samirelzein1095 Год назад

    amazing as usual!

  • @79JuanManuel
    @79JuanManuel Год назад

    Excellent explanation

  • @nisankarachandana6612
    @nisankarachandana6612 Год назад

    zing zing amazing explanation !!!!

  • @haushofer100
    @haushofer100 Год назад

    I like your videos a lot! Edit: removed confused question, solved it.

  • @shashankshekharsingh9336
    @shashankshekharsingh9336 9 месяцев назад +1

    amazed 🤯

  • @pseudounknow5559
    @pseudounknow5559 Год назад

    Excellent

  • @vaggelisntaloukas2016
    @vaggelisntaloukas2016 Год назад

    Thanks!

    • @SerranoAcademy
      @SerranoAcademy  Год назад

      Thank you so much for your contribution, Vaggelis! It’s really appreciated 😊

    • @vaggelisntaloukas2016
      @vaggelisntaloukas2016 Год назад

      @@SerranoAcademy it was a great tutorial, glad I discovered your channel

  • @haikvoskerchian2857
    @haikvoskerchian2857 2 месяца назад

    At 25:00 you said the fact that the poissonn distribution has 2 modes is an anomaly. But actually for every integer lambda, the poisson distribution has two modes. I wouldn't call that an anomaly.

  • @420_gunna
    @420_gunna Месяц назад

    4:26 "As N tends to infinity, the binomial distribution tends to the gaussian distribution, as per the CLT"
    This is not true, as far as I can tell. It tends to the poisson distribution.
    And the CLT is about the distribution of SAMPLE MEANS converging to a normal distribution as the number of sample means increases.
    Makes me worried about things that I'm not catching