I really love this series of statistic sagas, since everything i want to start a data analysis in excel or some other tools, these basic knowledge does help me with a better understanding of what i am doing
This is given by from one of my homework I’m currently working on, a formula for computing m & b: let vector x= [x1,...,xn]^T, y = [y1,...,yn]^T, matrix A =[x, [1,...,1]^T], then [m,b]^T=(A^T•A)^{-1} • A^T •y. If you move the matrix inverse from the right to left and then expand out the matrix multiplication, it actually gives you the system of equation at the end of the video. I couldn’t understand why at first, but your video explain this much well.
If u wonder where these derivatives came from, let me tell me there is another video a few videos after this one that should have been here in this place before this one. It is actually misplaced
because there are two variables (m,b). when y is a function of only one variable, e.g y=f(x), it's a 2D graph, and when y is a function of two variables, e.g y=f(x,z), it's a 3D graph.
I really love this series of statistic sagas, since everything i want to start a data analysis in excel or some other tools, these basic knowledge does help me with a better understanding of what i am doing
This is given by from one of my homework I’m currently working on, a formula for computing m & b: let vector x= [x1,...,xn]^T, y = [y1,...,yn]^T, matrix A =[x, [1,...,1]^T], then [m,b]^T=(A^T•A)^{-1} • A^T •y.
If you move the matrix inverse from the right to left and then expand out the matrix multiplication, it actually gives you the system of equation at the end of the video. I couldn’t understand why at first, but your video explain this much well.
To everyone who's wondering where part 2 is, here's the link; (can't post the link so here's the url after the .com: /watch?v=f6OnoxctvUk
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Elegant proof! Many thanks.
Thank you so much.
thanks
Really Love ❤️ your explanation...!!!
Thank you ...!!!
This is awesome, thanks Kan!
thanks! You're always the best
Excellent insight.
this playlist still needs some tidying up. Just move proof part 2 between part 1 and 3 please.
at 10:31 the "two" points are actually the same points (x_bar^2/x_bar, (x_bar * y_bar)/x_bar) is exactly (x_bar, y_bar)
no, it's not the same points..
It’s x^2_Bar not x_Bar^2. Remember that they are actually the sum of the n terms, so you can’t just cancel them out.
The conditions of partial derivatives being 0 will be true for maxima too. So then how will we know that our point is minima and not maxima?
this goes too fast for me, im going to rewatch x(
This playlist is out of order. Part 1 is #52, part 2 is #56, and part 3 is #53.
Watch Part 2 here before you follow part 3:
th-cam.com/video/f6OnoxctvUk/w-d-xo.html
If u wonder where these derivatives came from, let me tell me there is another video a few videos after this one that should have been here in this place before this one. It is actually misplaced
you're awesome
💯
how he decided,that the figure will be a 3D figure?
because there are two variables (m,b). when y is a function of only one variable, e.g y=f(x), it's a 2D graph, and when y is a function of two variables, e.g y=f(x,z), it's a 3D graph.