Mathematics, 13.01.2020 06:31 Dontslack

Agardener is designing a circular garden. on the blueprint, the garden has a diameter of 16 centimeters. the blueprint has a scale of two centimeters to five feet. what will be the actual area of the garden, in square feet, after it is built? round your answer to the nearest tenth of a square foot.

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Answer from: jaileen84

The actual area of the garden is 1256 square feet.

Step-by-step explanation:

Given:

A gardener is designing a circular garden.

On the blueprint, the garden has a diameter of 16 centimeters.

The blueprint has a scale of two centimeters to five feet.

Now, to find the actual area of the garden.

Let the actual diameter of the garden be $x\ feet.$

And the diameter of the garden on blueprint = $16\ centimeters.$

As, given:

The blueprint has a scale of two centimeters to five feet.

2 centimeters is equivalent to 5 feet.

Thus, 16 centimeters is equivalent to $x\ feet.$

Now, to get the actual diameter by using cross multiplication method:

$\frac{2}{5} =\frac{16}{x}$

By cross multiplying we get:

2x=80

Dividing both sides by 2 we get:

$x=40\ feet.$

Thus, the actual diameter of the garden is 40 feet.

Now, to get the area of the garden we get the radius and then put the formula of area:

Radius = $\frac{Diameter}{2}$

Radius(r)= $\frac{40}{2}=20\ feet.$

$Area =\pi r^2.$

$Area=3.14\times 20^2$

$Area=3.14\times 400$

$Area=1256\ square\ feet.$

Therefore, the actual area of the garden is 1256 square feet.

Answer from: Quest

What is your question?

Answer from: Quest

the answer is 200

step-by-step explanation:

this is a problem about poisson probabilities. i don't know if you've

already studied poisson distributions, or if you have a place to look

to read more about the subject.

here's how you can see a poisson distribution coming. when there are

a lot of events that may happen at any time (or any place), and when

you're counting how many of them happen at a particular time (or a

particular place), and each event is independent of the others, then

the result is a poisson distribution. this is roughly true for the

chocolate chips; one chip being in a cookie has only a small effect on

the probability that another chip will be in the cookie.

once you know you have a poisson distribution, you know a lot. there

is only one parameter to a poisson distribution, so if you know the

mean, you know everything. the form of the distribution is

probability of n chips = {[e^(-x)]*(x^n)} / (n! )

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