Answer:
(2) a rotation by 
about the intersection of the lines creating the vertical angles.
Step-by-step explanation:
Rigid motion are a set of transformation procedure to change the dimension, orientation or size of a given figure or shape. It involves rotation, translation, reflection and dilation.
Vertical angles are formed when two straight lines intersect to form angles. But two opposite angles called vertical angles are equal. To prove that vertical angles are equal; a rotation by about the intersection of the lines creating the vertical angles is required.
Hello there!
1. Okay. So 70% is positive, so it is a corresponding growth. 70% is 0.7 in decimal form. C and D are both eliminated, because that's too large. When something grows by 70%, that is less than double. 0.7 is not right either, because that's more of a decay than a growth. The only answer that makes sense id 1.70, because you are going up, and adding 1 to decimal form brings you to the decimal that when multiplied will bring you to the total. The answer is B: 1.70.
2. So, -75% is negative, so it is a decay factor. A is eliminated, because it makes no sense and B is out, because that represents growth, not decay. You lose 75% of the amount overtime compounded, but you still have 25% that remains. To find that amount, you would subtract that amount from 1 to get the decay. 1 - 0.75 is 0.25. The decay factor is 0.25. The answer is D: 0.25.
So, to solve this, we use this equation:
3700 + 0.05(3700)
But, if we want to make it shorter:
1.05(3700)
Now you just multiply(you may want to use a calculator)
1.05(3700) = 3885
She will pay $3885
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}.
The notation just means
(f/g)(-4) = f(-4) / g(-4)
If f(x) = x² + 2 and g(x) = 1 - 3x, then
f(-4) = (-4)² + 2 = 16 + 2 = 18
g(-4) = 1 - 3 (-4) = 1 + 12 = 13
and so
(f/g)(-4) = 18/13
