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Voiceover:We know that the multiplication
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of scalar quantities is commutative.
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For example, 5 times 7 is
the same thing as 7 times 5,
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and that's obviously just
a particular example.
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I could give many, many more.
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3 times negative 11 is the same
thing as negative 11 times 3
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and the whole point of commutativity ...
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I could never say it ...
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is that it doesn't matter what order
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that I'm multiplying in.
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This is the same thing
as negative 11 times 3.
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Or if we wanted to speak in general terms,
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if I have the scalar a and I
multiply it times the scalar b,
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that's going to be the same thing
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as multiplying the scalar
b times the scalar a.
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Now what I want to do in
this video is think about
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whether this property of commutativity,
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whether the commutative property
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of multiplication of scalars,
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whether there is a similar property
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for the multiplication of matrices,
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whether it's the case that
if I had two matrices,
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let's say matrix capital
A and matrix capital B,
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whether it's always the
case that that product,
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the resulting matrix here is the same
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as the product of matrix B and matrix A,
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just swapping the order.
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I encourage you ... so
is this always true?
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It might be sometimes true,
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but in order for us to say
that matrix multiplication
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is commutative, that it
doesn't matter what order
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we are multiplying it,
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we have to figure out is
this always going to be true?
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I encourage you to pause this video
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and think about that for a little bit.
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Let's just think through a few things.
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First of all, let's just
think about matrices
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of different dimensions.
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Let's say I have a matrix here.
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Let's say that matrix
A is a, I don't know,
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let's say it is a 5 by 2 matrix,
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5 by 2 matrix,
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and matrix B is a 2 by 3 matrix.
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The product AB is going
to have what dimensions?
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If I multiply these two, you're
going to get a third matrix.
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Let's just call that C for now.
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You're going to get a third matrix C.
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What are going to be the dimensions of C?
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We know, first of all, that
this product is defined
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under our convention of
matrix multiplication
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because the number of columns that A has
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is the same as the number of rows B has,
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and the resulting rows and column
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are going to be the rows
of A and the columns of B.
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So C is going to be a 5 by 3 matrix,
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a 5 by 3 matrix.
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Now what about the other way around?
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What would B times A be?
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Once again, I encourage
you to pause the video.
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If you were to take B,
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let me copy and paste that,
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and multiply that times A,
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so I'm really just switching
the order of the multiplication
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so copy and paste.
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If we take that product right over there,
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what is that going to be equal to?
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What is this?
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What is this right over
here going to be equal to?
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The first question is, is matrix
multiplication even defined
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for these two matrices?
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When you look at the number
of columns that B has
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and the number of rows that A has,
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you see that it actually is not defined,
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that we have a different
number of columns for B
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and a different number of rows for A.
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Here, the product is not defined,
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is not defined,
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so this immediately is a pretty big clue
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that this isn't always going to be true.
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Here, AB, the product AB is defined,
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and you'll end up with a 5 by 3 matrix.
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The product here, BA, isn't even defined.
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This is already ...
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We're already seeing that
this is not the case,
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that order matters when
you are multiplying,
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when you are multiplying matrices.
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To make things a little bit more concrete,
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let's actually look at a matrix.
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You might be saying, oh,
maybe this doesn't work
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only when it's not defined,
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but hey, maybe it works
if we're always to do
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square matrices or matrices
where both products
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are always defined in some way,
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or maybe some other case.
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Let's look at a case where we're dealing
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with 2 by 2 matrices and
see whether order matters.
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Let's say I have the matrix.
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Let's say I have the matrix
1, 2, negative 3, negative 4,
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and I want to multiply that by the matrix,
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by the matrix negative
2, 0, 0, negative 3.
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What's that product going to be?
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Once again, I encourage
you to pause the video
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and think about that.
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Let's think it through, and
we've done this many times now.
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This first entry here is going to be,
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we're essentially going to look
at this row and this column,
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so it's 1 times negative
2, which is negative 2,
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plus 2 times 0.
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This is going to be negative 2.
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Now, for this entry,
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for this entry over here,
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we'll look at this row and this column,
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1 times 0, which is 0,
plus 2 times negative 3,
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which is negative 6.
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Then for this entry, we
would look at this row
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and this column.
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Negative 3 times negative 2 is positive 6
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plus negative 4 times 0,
which is just positive 6.
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We're going to have positive 6.
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Then finally, for this entry,
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it's going to be the second
row times the second column.
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Negative 3 times 0 is 0.
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Negative 4 times negative
3 is positive 12,
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so fair enough.
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Now what if we did it
the other way around?
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What if we were to multiply
negative 2, 0, 0, negative 3
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times 1, 2, negative 3, negative 4?
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What's this going to be equal to?
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As always, it's a good
idea to try to pause it
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and work through it on your own.
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Let's think about this.
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Negative 2 times 1 is negative
2, plus 0 times negative 3,
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so that's going to be negative 2.
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So far, it's looking pretty good.
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Then if you have negative
2 times 2 is negative 4,
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plus 0 times negative 4 is negative 4.
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We already see that these two things
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aren't going to be equal,
but let's just finish it,
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just so that we have a
feeling of completion.
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This entry right over here is going to be
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the second row, first column,
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0 times 1 plus negative 3
times negative 3 is positive 9.
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Once again, it doesn't match up.
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Then finally, 0 times 2 is 0
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plus negative 3 times
negative 4 is positive 12.
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That one actually did match up,
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but clearly, these two products
are not the same thing.
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The order with which even those defined,
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it doesn't matter whether you take
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the yellow one times the purple one
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or the purple one times the yellow one.
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Both of those result in a defined product,
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but we see it's not the same product.
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Once again, another case showing
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that multiplication of
matrices is not commutative.