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}.
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It’s not exactly equal to one, but in many cases in math they ask for a rounded answer.
Answer:
Step-by-step explanation:
we know that
The simple interest formula is equal to
where
A is the Final Investment Value
P is the Principal amount of money to be invested
r is the rate of interest
t is Number of Time Periods
step 1
Find the rate of interest
in this problem we have
substitute in the formula above and solve for r
The rate of interest is 
step 2
Find the sum of money that will amount to 25,500 in 5 years, at the same rate of interest
in this part we have
substitute in the formula above and solve for P
