Mean, Variance, and Standard Deviation | Econometrics 101: Lesson 2.2 | Think Econ

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  • Опубликовано: 27 янв 2025

Комментарии •

  • @ThinkEcon
    @ThinkEcon  2 года назад +8

    Don't forget to check out the previous Econometrics 101 videos if you haven't already!

  • @jackcruickshanks
    @jackcruickshanks 2 года назад +11

    This series is terrific and I hope it will be returning very soon? Also, are these presentations available for download?

    • @ThinkEcon
      @ThinkEcon  2 года назад +1

      I am glad to hear that you enjoy it! We currently don't have the presentations available for download, but that may become a possibility in the future if there's a demand for it.
      Now that the school year has started back up, we should start releasing new videos for the series, with Lesson 2.3 scheduled to premiere tomorrow or Friday!

  • @_Ahmed_O
    @_Ahmed_O 2 года назад +4

    Thank you, we really need this course. 👍👍

  • @ikaosone1091
    @ikaosone1091 Год назад +1

    It’s amazing don’t quit the series

    • @ThinkEcon
      @ThinkEcon  10 месяцев назад +1

      We've started a pledge system to raise funds to continue the series since I know many people have found the first couple of episodes so valuable.
      Feel free to check it out at this link: www.ablebees.com/ssr/petitions/d8863414-971f-4893-abee-78104e5747d9

  • @haa542
    @haa542 Год назад

    Could you tell which book you might be using, I'd like if it is introduction to econometrics by James

  • @robertaversiani3355
    @robertaversiani3355 2 года назад +2

    great videos! thankyou !

    • @ThinkEcon
      @ThinkEcon  2 года назад

      Thank you for the feedback! We're glad you found it helpful :)

  • @davisclute7705
    @davisclute7705 2 года назад +2

    Great lesson, where is 2.3?

    • @ThinkEcon
      @ThinkEcon  2 года назад +1

      Thank you! Unfortunately we put the series on pause due to a lack of interest from viewers over the summer months

  • @zeyadelhalaby5282
    @zeyadelhalaby5282 2 года назад

    min: 9.20.. I guess I am lost here.. as I know more standard deviation determines the height and width of
    the curve. When the standard deviation is large, the curve is short and wide; when
    the standard deviation is small, the curve is tall and narrow. (high kurtosis)..did you mean that?

    • @ThinkEcon
      @ThinkEcon  2 года назад

      When we say "heavy tailed" we mean that a lot of data is concentrated in the tails of the distribution, and is further from the mean (therefore there are more outliers).
      What you're saying about the distribution being tall and heavily centred on the mean vs wide and more distributed is generally true, but it depends on the scale being used, so don't use that idea as a rule, but rather a guide, as it won't always be true.

  • @akuaagyeiwaa-afrane5223
    @akuaagyeiwaa-afrane5223 2 года назад +1

    Great

    • @ThinkEcon
      @ThinkEcon  2 года назад

      Glad you enjoyed the video!