Proof ols estimator is unbiased

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  • Опубликовано: 3 фев 2025
  • In this video we show that the Ordinary Least Squares estimator for beta 1 (the slope) is unbiased.

Комментарии • 30

  • @dylandejahang4345
    @dylandejahang4345 3 месяца назад +2

    I must say I never comment but this is the best video on the internet. I love the fact that you repeated things from the beginning throughout, it saved me having to go back and forth to remind myself what you are talking about. I hope more people post videos like you!

  • @paulmclean1268
    @paulmclean1268 3 года назад +23

    This is the BEST and EASIEST explanation I've found on this subject thus far. THANK YOU! much clearer!

  • @agustinlawtaro
    @agustinlawtaro 3 года назад +2

    I had problems understanding why the average y was null, and you explained it at 1:21. Many thanks!

  • @sionsterowzzz
    @sionsterowzzz 2 года назад +2

    man thank god for all the guys like you out here

  • @hazimkhaqanrana4875
    @hazimkhaqanrana4875 8 месяцев назад

    Thank you very much for this very detailed explanation. It helped a lot in my studies in Econometrics

  • @gabrielsmiley5067
    @gabrielsmiley5067 2 года назад

    Damn! You're a lifesaver. You decomposed everything to my understanding. Thanks🙏

  • @christopherbonadio-cappiel6773

    this video literally carried me on one of the questions on my econometrics exam lol

  • @benatchison8982
    @benatchison8982 Год назад +1

    THANK YOU, I HOPE YOU HAVE A GREAT YEAR

  • @guedes_133
    @guedes_133 9 месяцев назад

    You made something impossible look easy. thank you!

  • @AbdullaKaiksow
    @AbdullaKaiksow 2 года назад

    Thanks for this! It really helped

  • @PranayPaiPrannu
    @PranayPaiPrannu 9 месяцев назад

    Great video. Cheers!

  • @maccook9951
    @maccook9951 9 месяцев назад

    Top notch good sir!

  • @akwasiwireko2382
    @akwasiwireko2382 2 месяца назад

    Thanks so much man

  • @bsr4898
    @bsr4898 3 года назад

    thank you so much for explaining in details. regards

  • @janak6534
    @janak6534 3 года назад +1

    Hey, thanks for explaining it so well. Did I understand it correctly, that one could have another estimator of beta1 but as long as the assumption of the zero conditional mean is fulfilled at the end and a beta1 is in the sum before, the estimator will be unbiased?

  • @theemperor-wh40k18
    @theemperor-wh40k18 3 месяца назад

    The Xi's are not random, so why go trough all the trouble of using the LOTE? It is a linear term in the expectation. 10:36

  • @alejandrojara2024
    @alejandrojara2024 Год назад

    Thanks so much!!

  • @1UniverseGames
    @1UniverseGames 4 года назад

    Can you help with one thing to understand, like how we can obtain intercept and slope of B0 and B1 after shifting line l to l'?

  • @jessevickers4558
    @jessevickers4558 3 года назад

    Great videos

  • @qwkkk7172
    @qwkkk7172 2 года назад

    Did not understand why (xi -x bar) is not conditional on x... Please help

  • @Vasundhara-t7k
    @Vasundhara-t7k 4 года назад

    Did not understand at 7:53 why we had (Xi-X) equal to just Xi?

    • @easynomics880
      @easynomics880  4 года назад +3

      At 1:15 we showed this for sum(xi-xbar)(yi-ybar)=sum(xi-xbar)yi. At 7:53 it's just the same property sum(xi-xbar)(xi-xbar)=sum(xi-xbar)xi

  • @Crunchy257
    @Crunchy257 Год назад

    Var of Beta not Hat possess var of Beta 1 hat .solve this problem plz?

  • @Crunchy257
    @Crunchy257 Год назад

    Aoa can u Hepl me in one problem?

  • @gabrielsmiley5067
    @gabrielsmiley5067 2 года назад

    Easynomics>my lecturer🚶‍♂️

  • @ravitejathemacho
    @ravitejathemacho 2 года назад

    Explanation is too fast and not clear

  • @TheTsedeke
    @TheTsedeke 2 года назад

    pleas help me