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:
He gets 42 visitors 4 weeks after starting to build his website.
He gets 10 new visitors per week.
Step-by-step explanation:
Equation for the number of visitors:
The equation for the number of visitors Timmy's new website receives after t weeks is:
In which b is the number of visitors rightly after he starts.
Timmy is building a new website. Right after he starts, he has 2 visitors.
This means that 
, so:
How many visitors does he get 4 weeks after starting to build his website?
This is v(4). So
He gets 42 visitors 4 weeks after starting to build his website.
How any new visitors does he get per week?
After 0 weeks:
After 1 week:
2 weeks:
After 2 week:
22 - 12 = 12 - 2 = 10
He gets 10 new visitors per week.
Answer:
x = 2
Step-by-step explanation:
8x + 5 = 3x + 15
8x - 3x + 5 = 3x - 3x + 15
5x + 5 = 15
5x + 5 - 5 = 15 - 5
5x = 10
5x / 5 = 10 / 5
x = 2
The multiplier to get from 6 * ... to 15 is 15/6.
If 6 * 15/6 = 15, then 20 * 15/6 = 50, answer B.
Answer:
6(2) + 6(1) = 18
Step-by-step explanation:
