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}.
Hey there! :D
Slope intercept form: y=mx+b
4x-2y=9
Add 2y to the other side.
4x=9+2y
Subtract 9 on both sides.
4x-9=2y
Flip the equation over.
2y=4x-9 <== slope intercept form
I hope this helps!
~kaikers
Step-by-step explanation:
1. 1*1/6= 1 /6=1.67
2. 9*7/10= 63/10= 6.3
3. 7*4/8= 28/8= 3.5
4. 1/2 of 2= 1/2*2= 0.5*2= 1
5. 1/12 of 2= 1/12*2= 8.33*2= 16.66
6.2/6 of 2= 2/6*2= 3.33*2= 6.66
7. 1/3 of 5= 1/3*5= 3.33*5= 16.65
8. 3/10 of 8= 3/10*8= 0.3*8= 2.4
Hope it's help you ♥️
