1. Maximum Likelihood Estimation Basics

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  • Опубліковано 30 лип 2024
  • Maximum likelihood is a method of point estimation. This video covers the basic idea of ML.

КОМЕНТАРІ • 32

  • @HH-mo9ug
    @HH-mo9ug 6 років тому +19

    I need the MLE for my thesis in trade! You made it really clear and easy for me to understand! I literally didn't even know what that is and now I'll use it for my estimation. THANK YOU

  • @vince7079
    @vince7079 6 років тому +20

    Thank you! needed a quick recap and this helped. The software that you are using is amazing!

  • @mohammadalkadi8487
    @mohammadalkadi8487 6 років тому +6

    Great explanation. Thank you !

  • @richardparker6723
    @richardparker6723 6 років тому +3

    You are so awesome! I wish I could sit in your classrooms!

  • @tonio93tv
    @tonio93tv 6 років тому +115

    Do you actually write backwards?!?

    • @ProfessorKnudson
      @ProfessorKnudson  6 років тому +209

      I write normally (forwards) with my right hand. The software reflects the image. Pretty much every person (including me) wonders how it works when they see a video made this way.

  • @dannybutvinik8147
    @dannybutvinik8147 5 років тому +1

    Thank you! very presentative and intuitive explanation

  • @danieljimenezflores6041
    @danieljimenezflores6041 5 років тому

    Thanks for you great job ! It's so helpful.

  • @MrCigarro50
    @MrCigarro50 6 років тому +11

    Impressive...How do you do that. It is amazing. Well, Thank you, your videos are excellent.

  • @murtizaali3478
    @murtizaali3478 5 років тому +8

    Please make a vedio on "sufficiency or sufficient estimator ".

  • @arjun5458
    @arjun5458 5 років тому +2

    very helpful,thank you

  • @bergamobobson9649
    @bergamobobson9649 6 років тому +2

    i finally understnad it, thanks

  • @uroko2993
    @uroko2993 6 років тому +1

    Very helpful!

  • @louiswang538
    @louiswang538 6 років тому +283

    suggestion: dress black clothes..

  • @PasinduTennageprofile
    @PasinduTennageprofile 6 років тому

    Excellent explanation

  • @AndreaStevensKarnyoto
    @AndreaStevensKarnyoto 5 років тому

    you are amazing prof.

  • @govindashrit
    @govindashrit 6 років тому +4

    Thanks. Nice explanation.

    • @ProfessorKnudson
      @ProfessorKnudson  6 років тому +2

      You're welcome! I'm glad you got something out of it.

  • @danielbhc
    @danielbhc 5 років тому +4

    You used theta as the parameter here. Does this theta hold the same meaning as lambda for a Poisson distribution?

    • @danielbhc
      @danielbhc 5 років тому

      For example, you showed f(x|theta), would f(x|lambda) be valid too?

    • @ProfessorKnudson
      @ProfessorKnudson  5 років тому +9

      Yes, you can name the parameter whatever you want. It's like in a function: you can write f(x) or f(y) and it doesn't matter.

  • @RazikhShaik19
    @RazikhShaik19 6 років тому +4

    Super helpful tutorial! Thank you so much :)

  • @sharzilkhan9150
    @sharzilkhan9150 5 років тому +3

    i have tried to understand stats .. but not my cup of tea. :(

  • @mathematicswithjoy
    @mathematicswithjoy 5 років тому +2

    Nice

  • @edwardraywer4198
    @edwardraywer4198 5 років тому

    Thanks...

  • @pasqualenicolo4760
    @pasqualenicolo4760 6 років тому +5

    Thank u so much!

  • @pankajnegi9795
    @pankajnegi9795 6 років тому +1

    thank you!!

  • @faizanhussain1411
    @faizanhussain1411 5 років тому +3

    Thanks, I m from India.

  • @RohitKalia
    @RohitKalia 6 років тому +7

    wtf she writes backward