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}.
we have the price of TV is $3960.if we round off to the nearest tens we get same 3960 because we have 0 at the end which means lesser than 5 so 60 will be the nearest ten.
discount =
so $990 will be the discount.
and the cost of TV after discount is 
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46.2 dollars for the large necklaces and 14 dollars and seventy cents for the small necklaces therefore she will earn $60.9
Answer: $7200
Step-by-step explanation:
Given
The policy covers the damage of $50,000 PIP
He injured 10 people including himself
The total cost of injuries is $72,000
The cost per person is $7200
The company only pays for the damaged bear by the policyholder, not by the others.
the company only pays $7200 in coverage.
