Do you have a video about how to calculate u the mean squared error I am searching how to get it's equation mathematically Hope you could help Thank you From Algeria 🇩🇿
Hi Steve, Great work! And thanks for these videos. Quick question from me: the Beta vector that you defined when we had only one observation (10:58) versus for all the N obs (18:11) is different right? If yes, can I say, the one at 10:58 is a transpose of one at 18:11? Thanks.
@@stevel2037 Thanks Steve. Is the beta vector (at 10:58) a row vector or column? From your lecture, we wont be able to multiply x and beta vectors if they are both 1 by k+1 vectors. We can only multiple if beta is column vector or if beta vector is initialised as row vector then we transpose it.
@@엠제이-d7c it is actually one more than that - it is the number of beta parameters that need to be estimated (that’s why the “+1” is there - because of the intercept term B_0). K would be the number of independent variables.
You explained in 20min what my professor tried but failed to get across for 2 hours. Thank you!
Best explanation I've found online. Thanks!
So glad I found this. Thanks a lot Steve
This was fire, thank you
Amazing lecture
Explained so clear!!!
Excellent presentation - thank you very much.
This was fantastic!
Wonderfully explained. Great job
thank you
simply WOW. Thank you so much.
Thank you for this! I hate econometrics a little less now!
absolutely helpful
thank you!!!!
Super helpful! Thanks a lot~^^
which one is the next video guys?
Check out the playlist!
Do you have a video about how to calculate u the mean squared error
I am searching how to get it's equation mathematically
Hope you could help
Thank you
From Algeria 🇩🇿
Here you go: th-cam.com/video/EefPbiF9YRs/w-d-xo.html
@@stevel2037 Thanks I'am little bit struggling with MSE when it's with multiple variable so if you could help me with that it will be super kind :)
Imagine being a vector.
Hi Steve, Great work! And thanks for these videos. Quick question from me: the Beta vector that you defined when we had only one observation (10:58) versus for all the N obs (18:11) is different right? If yes, can I say, the one at 10:58 is a transpose of one at 18:11? Thanks.
Sure could. I don't make the distinction here since there are two vectors being multiplied.
@@stevel2037 Thanks Steve. Is the beta vector (at 10:58) a row vector or column? From your lecture, we wont be able to multiply x and beta vectors if they are both 1 by k+1 vectors. We can only multiple if beta is column vector or if beta vector is initialised as row vector then we transpose it.
@@richapandey7679 Nope - doesn't matter as long as the vectors are the same length.
You really need to be careful with matrices, not so much with vectors as the dot product of vectors can still commute (order doesn't matter).
@@stevel2037 Thanks.
What is K+1 term? to be specific what is exactly 'k' here?
I assume it is the number of independent variables in the model
@@엠제이-d7c it is actually one more than that - it is the number of beta parameters that need to be estimated (that’s why the “+1” is there - because of the intercept term B_0). K would be the number of independent variables.
@@stevel2037 wow, thanks!!!
Hi Steve, at 17:27 is the beta vector not supposed to contain beta hats instead of just beta?
Yes - PowerPoint wouldn’t let me put a hat and the vector symbol together, so I just used the vector symbol.
Are all the betas the same or different
Generally they are each different since each x variable has a different partial effect on the y variable.