Multicollinearity - Explained Simply (part 1)

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  • เผยแพร่เมื่อ 7 พ.ย. 2024

ความคิดเห็น • 26

  • @nuttyfruitloaf
    @nuttyfruitloaf หลายเดือนก่อน

    Your videos are so helpful! You make stats less scary. Thank you!

  • @how2stats
    @how2stats  11 ปีที่แล้ว +3

    With just two independent variables, yes, but if you have more than two independent variables, you need to consult the tolerance levels; they need to be higher than .10

  • @escapetothemoon9069
    @escapetothemoon9069 ปีที่แล้ว +1

    2023 lol this video is still worth to watch

  • @Std848
    @Std848 6 ปีที่แล้ว +4

    What should be the correlation threshold value based on which we determine the highly collinear variables?

  • @Value_Pilgrim
    @Value_Pilgrim 3 ปีที่แล้ว

    Wow! Understanding in 2 minutes. Thanks!

  • @Mista808
    @Mista808 5 ปีที่แล้ว +2

    I'm probably the only one here because I'm a writer and I'm trying to use this term in lyrics I'm writing.
    Please tell me if this even makes sense with the way I'm using it.
    Pico I need you I pray that you're here with me
    I cannot overcome this collinearity
    Pico is a friend of mine that recently took his life and when trying to rhyme
    "Pico I need you I pray that you're here with me"
    I couldn't think of a way to rhyme the end of the next line so I got on a rhyming
    website and the term Multicollinearity or collinearity rhymes perfectly with the
    line before it so I was trying to find a way I could possibly use it that actually
    makes sense and doesn't make the smart listeners think "wtf is he talking about?"
    lmao

    • @ninsiimaimmaculate4840
      @ninsiimaimmaculate4840 3 ปีที่แล้ว

      😂 probably. Do you suppose he still checks this video? Also sorry for your loss

  • @adameu1936
    @adameu1936 9 ปีที่แล้ว +1

    so in a nut shell if i had y= family income, and had some constant value, then beta 1 = husband income and beta 2= years of education of husband. you have multi collinearity because your basically double counting the same effect because husband income is strongly correlated with husband's years of education? so to fix you either have to combine the variables or drop one? thanks in advance for any help people :)

    • @himanshukush1246
      @himanshukush1246 6 ปีที่แล้ว +1

      Adam Eu thanks mate. You saved my 5 minutes😛

  • @risausa4796
    @risausa4796 ปีที่แล้ว

    Thanks for this helpful video!

  • @carolineheffernan2946
    @carolineheffernan2946 3 ปีที่แล้ว +1

    still don't get it :(

  • @khalidlaanani4365
    @khalidlaanani4365 10 หลายเดือนก่อน

    Simply explained!!!

  • @emanweri
    @emanweri 11 ปีที่แล้ว +1

    Wonderful explanation, thank you very!!!

  • @naftalibendavid
    @naftalibendavid 12 ปีที่แล้ว +2

    Superbly done!

  • @sly3xx
    @sly3xx 11 ปีที่แล้ว +2

    very clear! thank you so much.

  • @mihaicarnuta
    @mihaicarnuta 11 ปีที่แล้ว +1

    So, if there is a significant correlation between two or more IDs, but the r is less than .9 or .8, we shouldn't worry about it?
    Thank you!

  • @iqrasheikh4927
    @iqrasheikh4927 4 ปีที่แล้ว +5

    i just wanna slap that person so hard who introduced Econometrics subject.... God it is so difficult... i am cryingggg :(

  • @eteatestspreparation8129
    @eteatestspreparation8129 7 ปีที่แล้ว

    Plz tell me about Urdu econometrics videos

  • @mohammadsanaul5003
    @mohammadsanaul5003 8 ปีที่แล้ว +3

    what is beta weight??

    • @abhiksarkar9278
      @abhiksarkar9278 6 ปีที่แล้ว +2

      It the coefficient of X when we predict Y

  • @r3vath188
    @r3vath188 12 ปีที่แล้ว +1

    thank you so much.........

  • @statisticslearning
    @statisticslearning 2 ปีที่แล้ว

    Nice

  • @KiloNoah2
    @KiloNoah2 12 ปีที่แล้ว +1

    Thank you so much!

  • @YimingFaves
    @YimingFaves 10 ปีที่แล้ว

    so good to know!