Answer: The answer is 280 ft.
Step-by-step explanation:
divide the green area into a triangle and a rectangle so it's easier to calculate. Then find the area of the rectangle by multiplying 14 times 16. That should get you 224. Then, find the area of the tringle by multiplying 14 times 18, times 1/2. That will get you 56. If you add 56 to 224, that gets you 280.
Answer:
Hi there!
Your answer is:
Domino's waits to reveal the price until the end because, psychologically, you're predisposed to put & LEAVE more toppings on your pizza. If you see how each topping affects the price of the pizza each time you add one, you may limit the amount you choose. If you wait until the end to see it, by that point you think "Well I <em>need</em> these toppings on there to make it delicious." From a business standpoint, it's more financially beneficial to use the "hide the price until the end" system. However, from a consumer standpoint, most prefer seeing a live breakdown of how each topping affects the price so we can limit what we pay to a reasonable amount.
I hope this helps!
All you gotta do is subtract both of the numbers to get how much you need.
93 - 75 = 18
We can double check to see if it's right by using addition
18 + 75 = 93
Sonny needs to borrow 18$ to meet his required amount :D
Answer:
it is 1 2/10 but simplified to 1 1/5
Step-by-step explanation:
Answer:
A), B) and D) are true
Step-by-step explanation:
A) We can prove it as follows:
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B) When you compute the product Ax, the i-th component is the matrix of the i-th column of A with x, denote this by Ai x. Then, we have that
. Now, the colums of A are orthonormal so we have that (Ai x)^2=x_i^2. Then
.
C) Consider
. This set is orthogonal because
, but S is not orthonormal because the norm of (0,2) is 2≠1.
D) Let A be an orthogonal matrix in
. Then the columns of A form an orthonormal set. We have that
. To see this, note than the component
of the product
is the dot product of the i-th row of
and the jth row of
. But the i-th row of
is equal to the i-th column of
. If i≠j, this product is equal to 0 (orthogonality) and if i=j this product is equal to 1 (the columns are unit vectors), then
E) Consider S={e_1,0}. S is orthogonal but is not linearly independent, because 0∈S.
In fact, every orthogonal set in R^n without zero vectors is linearly independent. Take a orthogonal set
and suppose that there are coefficients a_i such that
. For any i, take the dot product with u_i in both sides of the equation. All product are zero except u_i·u_i=||u_i||. Then
then
.