Multiple Regression - Interpretation (3of3)

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  • Опубліковано 22 лип 2024
  • This video presents a summary of multiple regression analysis and explains how to interpret a regression output and perform a simple forecast.

КОМЕНТАРІ • 55

  • @odaialzrigat
    @odaialzrigat 4 місяці тому +1

    Thanks Dr. Pat Obi , unbelievably clear explanation , don't know why others over complicate these concepts!

  • @herodmoonga4799
    @herodmoonga4799 2 роки тому +5

    Yeah am grateful for your presentation, will fail no exam on this topic, thanks once more Sir, you are indeed a genius

  • @hendrika526
    @hendrika526 4 роки тому +6

    Seriously, these explanations are so clear and simply brilliant! Thank you so much!

  • @amantekle127
    @amantekle127 3 роки тому +13

    Watching this lecture is much better than attending my actual lectures online. Thank you!

    • @PatObi
      @PatObi  3 роки тому

      Thanks for your kind comment :-)

  • @kerrisonmarange3946
    @kerrisonmarange3946 4 роки тому +1

    Honestly i have been helped...thank you for providing such great clarity on the topic.#preps for my next month exams

  • @iamnotCorinne
    @iamnotCorinne 3 роки тому +1

    You, Sir, are a lifesaver. Thank you so much!

  • @andreatragni7528
    @andreatragni7528 11 місяців тому

    You are a wonderful and intelligent human being. Thank you

  • @aishakendrick4044
    @aishakendrick4044 5 років тому +33

    Thank you for breaking this down. I feel like partial cost of my PhD program should be paid to UA-cam (that's bad I know).

    • @PatObi
      @PatObi  3 роки тому +1

      You're very welcome!

    • @aidylmorningdew195
      @aidylmorningdew195 3 роки тому +1

      @@PatObi me too. UA-cam has helped me a lot during my PhD journey

  • @toseefdin5521
    @toseefdin5521 2 роки тому

    Oh My - so nice to see this video- you were in the strathmore uni orientation day...i am happy to see you here professor

  • @mukailarafiu2718
    @mukailarafiu2718 3 роки тому +3

    This presentation is phenominal. May God bless you, sir.

    • @PatObi
      @PatObi  3 роки тому +1

      Thank you. And you too.

  • @itismitabiswal7675
    @itismitabiswal7675 4 роки тому +1

    Thank you so much really.....so simple explanation..that no body can give..

  • @Guilopes99
    @Guilopes99 4 роки тому

    Do you have any tips on excel to:
    - select the right variables
    - check if the required assumptions are match
    - checking outliers and missing values
    - how to test several combinations of variables

  • @RonanJoyce123
    @RonanJoyce123 3 роки тому +1

    i am doing a question comparing 2 models which each have 3 independent variables. Can i use the fact that Model 2 has a lower standard error of the estimate than Model 1 as a predictor of the dependent variable?.. since this would mean narrow the width of the confidence interval and therefore give smaller margin of error in my prediction of the dependent variable?
    Thanks

  • @wengelawitbisrat8934
    @wengelawitbisrat8934 2 роки тому

    Thank you.
    I was doing analysis and i got beta value positive 0.026 but the sig.value is 0.6. So should i reject the hypothesis ? Does it mean x and y are negatively related ?

  • @brendanyarko2536
    @brendanyarko2536 2 роки тому

    what do i do if my r square is less 10% but the model is significant?

  • @42laar
    @42laar Рік тому

    thank you so much for the thorough explanation!

  • @evelynfurtado1240
    @evelynfurtado1240 2 місяці тому

    If i have a model where the p value as a whole is not significant, but one independent variable is significant, can it still be reported?

  • @shanuibra
    @shanuibra Рік тому

    Sir if R square in regression model will around . 2 or. 3 is it problematic?

  • @malloryalvacastaneda2547
    @malloryalvacastaneda2547 2 роки тому

    Hello Sir, where did you get the number x1=52 and x2=17? maybe i have missed it on your presentation. thank you

  • @markosmanaye5578
    @markosmanaye5578 8 місяців тому

    Very helpful presentation. Thankyou sir!

  • @collinsagayi2233
    @collinsagayi2233 3 роки тому

    Wow. Thanks a lot. Now I can interpret my data very well

    • @PatObi
      @PatObi  3 роки тому +1

      You're welcome!

  • @tsehayenegash8394
    @tsehayenegash8394 Рік тому

    How can we calculate the error term

  • @somcana
    @somcana 4 роки тому +1

    Thanks Pat!

  • @Guilopes99
    @Guilopes99 4 роки тому +5

    Probably the best clear yet more in depth explanation on the interpretation. So good!
    Do you normalize data before the regression? Does it matter? Thanks

    • @PatObi
      @PatObi  4 роки тому +1

      Thanks for your kind comments. No, I don't think it's necessary or even appropriate to normalize regression data. Just my opinion :)

    • @PatObi
      @PatObi  2 роки тому

      No need to normalize unless you wish to. Sorry for late response :-)

  • @SandeepKumar-sg7ou
    @SandeepKumar-sg7ou 8 місяців тому

    To estimate the Marginal Value Product (MVP) and Marginal factor cost (MFC) equated to allocative efficiency ratio or from regression coefficient of the variables

  • @ronelnature1792
    @ronelnature1792 3 роки тому

    Good work 🤝

  • @Mandla89
    @Mandla89 3 роки тому

    Thank you so much for this

  • @AKAxdkid_
    @AKAxdkid_ 2 місяці тому

    Thanx a lot , i can now her heart❤️

  • @beckienantongo2424
    @beckienantongo2424 Рік тому

    Thnx. Very helpful video

  • @francisbenath2309
    @francisbenath2309 3 роки тому

    thanks lo for every words...

  • @ladoucefleur1748
    @ladoucefleur1748 4 роки тому +1

    Thank you so much

  • @patricialuize
    @patricialuize 3 роки тому +1

    Thank you so much, Sir! Your videos are very helpful!

    • @PatObi
      @PatObi  3 роки тому

      You're welcome!

  • @thebiglad
    @thebiglad 2 роки тому

    Top guy Pat

  • @Gorrdo4
    @Gorrdo4 11 місяців тому

    Thank you Sir.

  • @ttanchor3254
    @ttanchor3254 2 роки тому

    Verry helpful

  • @lorenzomiguelgarcia842
    @lorenzomiguelgarcia842 3 роки тому

    Is there a way to determine if one of the independent variables moderates the relationship of the other independent variable and the outcome using multiple linear regression?

    • @PatObi
      @PatObi  3 роки тому

      I'm not sure, Lorenzo, except perhaps in the context of colinearity and in a different case, inclusion of interaction terms. Please ask others.

  • @davinsanch
    @davinsanch 10 місяців тому

    I owe you!

  • @dinaraniyazova7323
    @dinaraniyazova7323 3 роки тому

    Hello! How to calculate p test manually? is there is formula in multiple regression?

    • @PatObi
      @PatObi  3 роки тому

      You can watch the 2nd half of this video: ua-cam.com/video/k07RULqaFOk/v-deo.html

  • @kemenuwapaul5761
    @kemenuwapaul5761 4 роки тому

    my god will bless u

    • @PatObi
      @PatObi  4 роки тому

      Thank you.

  • @gardeningtourfamilycelebra8268
    @gardeningtourfamilycelebra8268 3 роки тому

    sir please help me
    my problem is -
    Another persons explain his model -
    RSEI = 0.098*NDVI + 1.019*WET - 0.025*NDSI - 0.001*LST + 0.007 (R2 =0.998)
    1. The WET must increase by 0.098 if the RSEI increase by 0.1. Nevertheless, the increased WET and the decreased LST occurred at the same time .
    2. Therefore, RSEI increase will be more than 0.1. If the LST decrease by 0.098 and the WET increased by 0.098 the RSEI will increase by 0.10001.
    How its explain?
    My model is -
    RSEI = 0.9396*NDVI - 0.0074*WET - 0.22496*NDSI + 0.04665*LST + 0.0664 (R2 =1)
    So,1. If the RSEI increase by 0.1 then NDVI must increase ................?
    2. RSEI will increase by 0.10001, Then LST decrease by .................? and NDVI increased by ..................................?
    How this model explain above mention two point?
    Please answer me. and help me.

    • @PatObi
      @PatObi  3 роки тому

      Please watch my short video, Regression - In Brief 2of3, for interpretation of regression result. In your study, RSEI rises(falls) by 0.098 unit for every 1 unit increase(decrease) in NDVI, with the other variables held constant.

    • @gardeningtourfamilycelebra8268
      @gardeningtourfamilycelebra8268 3 роки тому

      Sir please send your 2 of 3 video link. because I want to interpreted my model. thank you sir.

    • @gardeningtourfamilycelebra8268
      @gardeningtourfamilycelebra8268 3 роки тому

      Sir RSEI is the dependent veritable and other WET, LST, NDSI, and NDVI is the independent veritable. I am calculated multi regression. but i can not explain the model. sir I want to explain my model.

  • @bepultalimschool5171
    @bepultalimschool5171 2 роки тому

    Can you send me this ppt or docx