20. Central Limit Theorem

Поделиться
HTML-код
  • Опубликовано: 1 окт 2024
  • MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010
    View the complete course: ocw.mit.edu/6-0...
    Instructor: John Tsitsiklis
    License: Creative Commons BY-NC-SA
    More information at ocw.mit.edu/terms
    More courses at ocw.mit.edu

Комментарии • 20

  • @raksahv7860
    @raksahv7860 2 года назад +10

    Thank you Sir, Just wanted to say thank you, for giving me a deeper insight into probability. I studied this from the 1st lecture to this. I will study the last 5 lectures later on.

    • @TCS_School
      @TCS_School 2 года назад +3

      The same for me, it was an amazing experience in the intuitive understanding of some of probability theory terminology. Also his co-author textbook is so valuable and in the book they gave CLT as the last thing.

  • @BoutinMathieu
    @BoutinMathieu 9 лет назад +27

    An error is made at 21:50, but is then corrected at 23:48.

    • @aniruddhnls
      @aniruddhnls 6 лет назад

      at 15:02 he says the pmf's have approximated to normal. Before at 9:16 he said pmt's do not approximate.????

    • @vivekrai1974
      @vivekrai1974 4 года назад +1

      @@aniruddhnls This is because at 9:16 he takes n =8 and at 15:02 he takes n = 16 and more. In a nutshell, (as he explains later), if the distribution is skewed you have to take a larger n to approximate normal distribution.

  • @barbazzfoo
    @barbazzfoo 4 года назад +8

    this prof is so good at lecturing

    • @Adityarm.08
      @Adityarm.08 Год назад +1

      +1, i didn't really like statistics, but this lecture series has completely changed it for me.

  • @xueqiang-michaelpan9606
    @xueqiang-michaelpan9606 7 лет назад +6

    the puzzle is really good!

  • @teddonaville1151
    @teddonaville1151 2 года назад +1

    i only understood pdf

  • @limzphotography4363
    @limzphotography4363 2 года назад +1

    In love with course outline

  • @alejandromaciel8031
    @alejandromaciel8031 10 месяцев назад

    godly lecture skills. what a man

  • @Starr169
    @Starr169 9 лет назад +4

    One of my students suggested a short cut to calculate probability P(Z>2) without using 1-P(Z2) is equal to P(Z

    • @shailendrapatil994
      @shailendrapatil994 8 лет назад +2

      Thats true because we assume a normal distribution and as it is symmetric , the value will be the same

    • @nathansherrard4111
      @nathansherrard4111 7 лет назад +9

      The potential issue is that most normal tables only show Z >= 0, accounting for that symmetry to save table space.

    • @aniruddhnls
      @aniruddhnls 6 лет назад

      at 15:02 he says the pmf's have approximated to normal. Before at 9:16 he said pmt's do not approximate.????

    • @rajinfootonchuriquen
      @rajinfootonchuriquen 2 года назад +1

      @@aniruddhnls watch all the lecture. He literally explain that pmf of Bernoulli is a special case

  • @billmichae
    @billmichae 3 года назад

    Excellent Prof!!! ElGrecoProf++

  • @MohdZaid-cl3cg
    @MohdZaid-cl3cg 5 лет назад

    how is standard deviation is f(1-f)..at 19:40 ???

    • @mohamedlehbib7116
      @mohamedlehbib7116 4 года назад +1

      It is 9 month later but f(1-f) because we have a binomial distribution with a mean equal to f, so the variance would be f(1-f)