You probably already have an idea of what a matrix is; it's a rectangular array of numbers. What they represent is a bit complicated to explain. There's a whole subject about it (see "linear algebra" for more info). Whatever they represent isn't important though, you don't need to know everything about matrices to compute their product (or whether it's even possible).
A quick definition: A matrix of dimension -by-
is a matrix with
rows and
columns.
Matrix multiplication all comes down to an operation called the "dot product". It's defined by the sum of component-wise products of elements between two lists. What this means is, if and
, then the dot product of
and
is
What we did was take the first elements of each list and multiplied them, and the same for the other two elements, then added them all together. Notice that the product can't be computed if and
don't thave the same number of elements.
We write this product in matrix form as
Notice the pattern here: on the left, a matrix with 1 row and 3 columns; on the right, a matrix with 3 rows and 1 column. The number of columns of the first matrix have to match the number of rows of the second.
The orientation makes a big difference. The product above returns a 1-by-1 matrix (or simply a scalar number):
On the other hand, the alternate orientation would result in a 3-by-3 matrix.
So the number of rows of the first matrix and number of columns of the second matrix determine the number of rows and columns, respectively, of the matrix product.
I think we have enough information about matrix multiplication to answer this question. If has dimensions
and
has dimensions
, then the matrix product
exists (
columns in
,
rows in
), but the matrix product
does not (
columns in
,
rows in
, but
). So I is not true.
We know exists, and with
rows in
and
columns in
, we expect
to have
rows and
columns, so
has dimensions
. So II is true.
With dimensions , a matrix would contain
elements.
are distinct, so
. So III is not true.