This is amazing, thank you so much! Finally can link theory from my lectures with intuition behind the concepts! It would be amazing if u made a similar video on generalised linear models
I have a bachelors in Economics and a masters in Bussiness analytics, and this helped me connect a lot of dots between all my knowledge so far, to develop intuition behind how a linear regression actually works. I was trying to understand the intution behind why adding more variables in a linear regression helps "explain" the variation of the dependent variable. I think the answer is that when you add a new variable, you are creating a different "line" for which you are trying to estimate the beta coefficients that minimize the residuals. By adding a new variable, you are perhaps able to capture more of the variance of y, because you perhaps calculate a line that is closer to the true regression. By adding too many variables (non counfounders), you are adding unecessary noise that is creating bias in your estimation of the regression.
Here’s a tip. In practice, you can create scatter plots of new variables plotted on x and the variance of your multi linear regression model on y. To find more variables to explain the variance in your model
Your explanation is simple and clear to understand. You are better than my professor. Thanks for your videos.
Wow I’m so lucky to find this video, concise and to the point! Thank you
That's why I never attend class in-person
Yeah me too ,,,,,,,, wandering around about a week
How beautiful! I loved linear algebra in college. What a great refresher
This question has already bothered me 40 hours.
Thanks to this good video ,I love it.😍😍😍
This is amazing, thank you so much! Finally can link theory from my lectures with intuition behind the concepts! It would be amazing if u made a similar video on generalised linear models
same bruv. My professor used the matrix approach and I didn't understand shit.
Thank you, this is exactly what I was looking for!
I have a bachelors in Economics and a masters in Bussiness analytics, and this helped me connect a lot of dots between all my knowledge so far, to develop intuition behind how a linear regression actually works. I was trying to understand the intution behind why adding more variables in a linear regression helps "explain" the variation of the dependent variable. I think the answer is that when you add a new variable, you are creating a different "line" for which you are trying to estimate the beta coefficients that minimize the residuals. By adding a new variable, you are perhaps able to capture more of the variance of y, because you perhaps calculate a line that is closer to the true regression. By adding too many variables (non counfounders), you are adding unecessary noise that is creating bias in your estimation of the regression.
This was very good learning material and well demonstrated steps. Thank you very much!
A very good explanation indeed!
Here’s a tip. In practice, you can create scatter plots of new variables plotted on x and the variance of your multi linear regression model on y. To find more variables to explain the variance in your model
Excellent content.
Thank you so much for the lecture!
Best! Very helpful video.
Thank you, you saved my life :)
I love this guy
Thank you so much!! That is so helpful for me
Thanks a lot
thank youuu
omg thank you so much 😭😭😭😭!!!!!
THANK YOU SO MUCH!
Which is book
Where Can I get your next video
Here's the playlist: ruclips.net/p/PL4xAk5aclnUjdC0bnZuizleV0MR6LRvrP