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erastovalidia [21]
3 years ago
9

Snow Dome Ski Resort has 65 inches of snow. It is currently snowing there at a rate of 1 inch per hour. Mt. Winterpark Ski Resor

t has 74 inches of snow. Currently it is snowing there at a rate of ½ inch per hour.
a) Write equations that show the amount of snow at each resort as a function of the number of hours of snow.

b) If the snow continues at this rate, when will Snow Dome have more snow than Mt. Winterpark? Show your solution process clearly.
Mathematics
1 answer:
xz_007 [3.2K]3 years ago
8 0

Answer:

(a)

Snow Dome Ski: y = 65 + t

Mt. Winterpark: y = 74 + ½t

(b) Hours greater than 18

Step-by-step explanation:

Given

Snow Dome Ski

Base Snow = 65in

Rate = 1 in per hour

Mt. Winterpark

Base Snow = 74 in

Rate = ½ in per hour

Solving (a): Equation for both

To determine the amount of snow (y) at time (t) for any of the two, we make use of:

y = Base Snow + Rate * t

For Snow Dome Ski:

y = 65 + 1 * t

y = 65 + t

For Mt. Winterpark

y = 74 + ½ * t

y = 74 + ½t

Solving (b): When snow dome will have more snow.

To solve this, we set the following inequality

Snow Dome Ski > Mt. Winterpark

This gives:

65 + t > 74 + ½t

Collect Like Terms

t - ½t > 74 - 65

½t > 9

Multiply both sides by 2

t > 18

This implies that the snow at Snow Dome Ski will be more than the snow at Mt. Winterpark after 18 hours.

After 18 hours means, hours greater than 18 which could be 19, 20, 21.....

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3 years ago
A manufacturer considers his production process to be out of control when defects exceed 3%. In a random sample of 100 items, th
pochemuha

Answer:

The p-value of the test is of 0.2776 > 0.01, which means that the we accept the null hypothesis, that is, the manager's claim that this is only a sample fluctuation and production is not really out of control.

Step-by-step explanation:

A manufacturer considers his production process to be out of control when defects exceed 3%.

At the null hypothesis, we test if the production process is in control, that is, the defective proportion is of 3% or less. So

H_0: p \leq 0.03

At the alternate hypothesis, we test if the production process is out of control, that is, the defective proportion exceeds 3%. So

H_1: p > 0.03

The test statistic is:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the value tested at the null hypothesis, \sigma is the standard deviation and n is the size of the sample.

0.03 is tested at the null hypothesis

This means that \mu = 0.03, \sigma = \sqrt{0.03*0.97}

In a random sample of 100 items, the defect rate is 4%.

This means that n = 100, X = 0.04

Value of the test statistic:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

z = \frac{0.04 - 0.03}{\frac{\sqrt{0.03*0.97}}{\sqrt{100}}}

z = 0.59

P-value of the test

The p-value of the test is the probability of finding a sample proportion above 0.04, which is 1 subtracted by the p-value of z = 0.59.

Looking at the z-table, z = 0.59 has a p-value of 0.7224

1 - 0.7224 = 0.2776

The p-value of the test is of 0.2776 > 0.01, which means that the we accept the null hypothesis, that is, the manager's claim that this is only a sample fluctuation and production is not really out of control.

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3 years ago
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Wym? Like what kind of graph is it?
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ladder 5m tall when set against a wall of house just reach the window at a height 3m how far is the lower end of ladder from the
KATRIN_1 [288]

Answer:

4

Step-by-step explanation:

A simple matter of using Pythagoras. The hypotenuse is the ladder, and one of the legs is the wall, and we have to figure out the value of the other leg.

The Pythagorean formuda is (hypotenuse = a): a² + b² = c² (b and c are the other sides)

applying the values: a = 5 and b or c is 3 (I'll put b = 3)

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√16 = c

4 = c

c = 4

3 0
3 years ago
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