D-Separation

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  • Опубліковано 14 січ 2025

КОМЕНТАРІ • 8

  • @actruce
    @actruce 3 роки тому

    Thanx for making this video! I finally understand the algorithm how to select d-separation

  • @alexiscanari8776
    @alexiscanari8776 3 роки тому

    Thank you so much!!! your explanation is great!! Could you maybe please do a video about potential outcomes. I trying to understand it but I have been some struggles. Thank you so much and continue doing these amazing videos!!! :)

    • @lesliemyint1865
      @lesliemyint1865  3 роки тому +1

      I'm glad this was helpful! I have a video that explains potential outcomes in the context of defining what causal effects are: ua-cam.com/video/poSGgCFsHgU/v-deo.html. Hopefully that helps!

    • @alexiscanari8776
      @alexiscanari8776 3 роки тому

      @@lesliemyint1865 that'samazing , thank you so much!!

  • @programmingwithjackchew903
    @programmingwithjackchew903 2 роки тому

    hi i was wondering what is the criteria you determine this graph belongs to non causal graph? is it more than 1 structure to compose the graph belong to non causal for example combination of fork and chain is belong to non-causal graph?

    • @lesliemyint1865
      @lesliemyint1865  2 роки тому

      To clarify, it is not a *graph* that is causal or noncausal, but rather *paths* within a graph. I'd recommend watching some of the earlier videos in this playlist: ua-cam.com/play/PLtjTgbI6JvXZ-rrZ9FOLG37IWwoyR1GcF.html. (In particular, the videos titled "Introduction to Causal Graphs", "Causal Graphs as Statistical Models", "Key Structures in Causal Graphs", and "Causal and Noncausal Paths."

  • @FelipeSanhueza94
    @FelipeSanhueza94 3 роки тому

    Thanks ! great explanation

  • @yulinliu850
    @yulinliu850 3 роки тому

    👍❤🎉