Rowspace and left nullspace | Matrix transformations | Linear Algebra | Khan Academy

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Rowspace and Left Nullspace
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[@GeorgeNavarro]

Thank you for this. My professor never actually taught us this and is putting it on the exam I am taking in an hour

[@gustavovbarroso]

Much needed review, just in time. Great vid!

[@kevinmm20]

What a great explaination! See, you understand this and were able to explain this perfectly. Now that I understand it, this stuff isn't that difficult. So why is it that some text books and teachers like to make it difficult!?

[@davidsalcido1257]

Good job teaching..!

[@debendragurung3033]

17:51; so that's the actual reason for the term LEFTNULLSPACE

[@Nishchay-fk5lr]

g strang teaches a bit hazy

[@parnashish1910]

Beautiful :)

[@lemyul]

I wish I understand the book as much as I understand watching this video.

[@lutherhoward7637]

Because you are not concentrating when you read. Reading math and physics books takes total concentration and reading sections more than once. Then, writing the concepts in your own words. Or teach it to someone. Lincoln studied by reading out loud.

[@HotPepperLala]

As much I as thank you for this video, you really didn't need to extend this for 23 mins, especially when the first 8 minutes is just review and you could have prepared the rref(M) ahead of time. I miss your straightforward videos in the past.

[@mky3405]

At 14:45, does Sal mean "column space of the R transpose matrix"? if not, what is "column span"? He sometimes says "column span", and it confused me.

[@Rovshenification]

Thank you for this video. But I have a one question. We can determine the basis by number of vectors in our Matrix, right? For ex., we have three vectors (column) in matrix, thus dimension should be 3D space, yes?

[@Postermaestro]

+Rovshen A-ev You can determine the basis of the column space of a matrix by counting the number of pivot entries in our reduced row echelon form of the matrix. If you have 3 pivot entries in your rref-matrix, that means that you have 3 linearly independent column vectors in your matrix. Thus, the dimension of the column space of the matrix is 3, or in other terms: the rank of the matrix is 3.

[@fuahuahuatime5196]

Hey I have a question. How can you find the zero vector of a basis U with respect to the standard basis E?

[@tis_i_sana]

hm interesting question

[@sanjaykrish8719]

U are my God..

[@Philips85281]

Why you always choose simple matrix which simplified only 1 row left????

[@ionglacier]

crap dammit! why can't you be my proffesor???

[@dupham7900]

why name the video rowspace and left null space ? and then go on to explain column space, and barely anything about rowsapce

[@QuickishFM]

because the rowspace is just the column space of the transposed matrix of A. You just find the column space again for the transposed matrix, which is the row space for the original non-transposed matrix

[@malharjajoo7393]

explanation is not helpful