In linear algebra, the rank of a matrix
A
A is the dimension of the vector space generated (or spanned) by its columns.[1] This corresponds to the maximal number of linearly independent columns of
A
A. This, in turn, is identical to the dimension of the vector space spanned by its rows.[2] Rank is thus a measure of the "nondegenerateness" of the system of linear equations and linear transformation encoded by
A
A. There are multiple equivalent definitions of rank. A matrix's rank is one of its most fundamental characteristics.
The rank is commonly denoted by
rank
(
A
)
{\displaystyle \operatorname {rank} (A)} or
rk
(
A
)
{\displaystyle \operatorname {rk} (A)}; sometimes the parentheses are not written, as in
rank
A
{\displaystyle \operatorname {rank} A}.
Answer:
31/3 ×51/4
527/4
Step-by-step explanation:
It would be 6 because it it under .5 so you wouldn't round up
To answer this, we need to use the rules of geometric shapes. An equilateral triangle is equiangular, meaning all its angle measures are equal. Since all triangles' angles add up to 180°, simply divide 180 by three to find the angle measure of each angle:

Therefore, the measure of the triangle's angle is
60°Next, we know that a characteristic of a rectangle is that each angle must be a right angle, or an angle with a measure of
90°.
Now, all we have to do is use the sum of all the angle measures to figure out the missing piece:

The missing angle measure, angle
x, equals 18°.
Hope this helps!