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djyliett [7]
3 years ago
10

Answer ASAP. Please give correct answer. (Involves a bunch of circles and trig identities)

Mathematics
1 answer:
iren [92.7K]3 years ago
7 0

Answer:

45.40

Step-by-step explanation:

First of all, the shape of rope is not a parabola but a catenary, and all catenaries are similar, defined by:

y=acoshxa

You just have to figure out where the origin is (see picture). The hight of the lowest point on the rope is 20 and the pole is 50 meters high. So the end point must be a+(50−20) above the x-axis. In other words (d/2,a+30) must be a point on the catenary:

a+30=acoshd2a(1)

The lenght of the catenary is given by the following formula (which can be proved easily):

s=asinhx2a−asinhx1a

where x1,x2 are x-cooridanates of ending points. In our case:

80=2asinhd2a

40=asinhd2a(2)

You have to solve the system of two equations, (1) and (2), with two unknowns (a,d). It's fairly straightforward.

Square (1) and (2) and subtract. You will get:

(a+30)2−402=a2

Calculate a from this equation, replace that value into (1) or (2) to evaluate d.

My calculation:

a=353≈11.67

d=703arccosh257≈45.40

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IN THE LAST TWO WEEKS , A PLANT GREW 1/16 IN. AND 3/16 IN. RESPECTIVELY
grandymaker [24]
I'm assuming you mean that the plant grew 1/16th of an inch the first week, and 3/16th of an inch the next week. Simply add the two together (4/16th) and simplify. Since four goes into both numbers, the simplified version is 1/4th. Hope this helps
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4 years ago
The weight of crackers in a box is stated to be 16 ounces. The amount that the packaging machine puts in the boxes is believed t
krek1111 [17]

Answer:

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\mu = 16.15, \sigma = 0.3, n = 50, s = \frac{0.3}{\sqrt{50}} = 0.0424

What is the probability that the mean weight of a 50-box case of crackers is above 16 ounces?

This is 1 subtracted by the pvalue of Z when X = 16. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{16 - 16.15}{0.0424}

Z = -3.54

Z = -3.54 has a pvalue of 0.0001

1 - 0.0001 = 0.9999

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

3 0
3 years ago
CA=2,AB=3, The angle of C=90 degrees what is the angle of B?
Levart [38]

Answer:

m∠B ≈ 41.81°

Step-by-step explanation:

If we draw a picture, it would help a lot. Once we visualize the triangle, we can see that we have sin∅ = 2/3. So, plugging into your calc,

sin∅ = 2/3

∅ = sin^-1(2/3)

∅ = 41.8103

5 0
3 years ago
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