9.36 oh dear,which “previous theorem”you’re referring to?I have no idea of that,not in the least mate!Would you mind to refer me to a link of that video or something else?
so at 5:03 wouldnt that matrix be no solution since the last row is 0 0 0 5? hence one to one, or do we just go by the rows(onto) and cols(one to one) of pivots for the answer?
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Is there any possibility I can press several likes to this single video? And the rest from the playlist! What a smart man! Much respect
Very Detailed and Explanatory.
Much appreciated 💯
Thank you so much sir 💛
At 4:41, why we consider the number 5 as a pivot?
The pivots are the leading entries in each row, when the matrix is in echelon form.
clear and nice
Can someone explain how the matrix A having a pivot in each row will make it so that Ax=b will have a solution for every b?
I answer this question in Lecture 9: th-cam.com/video/OyqOfbeEhL0/w-d-xo.html
@@HamblinMath Thanks for the guidance. I watched that lecture yesterday but will definitely take another look.
9.36 oh dear,which “previous theorem”you’re referring to?I have no idea of that,not in the least mate!Would you mind to refer me to a link of that video or something else?
This theorem from Lecture 9: th-cam.com/video/OyqOfbeEhL0/w-d-xo.html
so at 5:03 wouldnt that matrix be no solution since the last row is 0 0 0 5? hence one to one, or do we just go by the rows(onto) and cols(one to one) of pivots for the answer?
That's not an augmented matrix. Think carefully about what the pivots in the matrix represent and what they tell you about related matrix equations.