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Alex73 [517]
3 years ago
5

A lighthouse beacon can be seen 17mi in all directions. To the nearest square mile, what is the area over which the beacon can b

e seen?
Mathematics
1 answer:
Alchen [17]3 years ago
7 0
Imagine this as a circle. The circle will have a radius of 17mi and the lighthouse will be in the middle. The area of the circle will be the area over which the beacon can be seen.

A=\pi  r^{2} is the equation for the area of the circle where A is the area.

Now we simply plug in our information

A=\pi  (17)^{2}
A=907.9mi^{2}
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Picking a blue marble from a bag of 4 red marbles, 6 blue marbles, and 1 white marble
salantis [7]
You have a 1:11 ratio of choosing a blue marble from a bag of 4 <span>red marbles, 6 blue marbles, and 1 white marble.</span>
6 0
3 years ago
Simplify the problem.
lesya [120]

Answer:

Option 4: 4¹¹

Step-by-step explanation:

Looking at the problem, I need to work out 4⁴ squared first, which is the same as 4⁸. Then multiply that by 4³ to get 4¹¹. What I did was simply add 3 + (4 * 2), which is 11.

7 0
3 years ago
Only number 5 please help
Ilya [14]
B. 60 this can be answered by also knowing degree angle's as it starts at 0 increments of 10
7 0
2 years ago
The mean of a population is 74 and the standard deviation is 15. The shape of the population is unknown. Determine the probabili
Lena [83]

Answer:

a) 0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

b) 0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c) 0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

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 normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, 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.

The mean of a population is 74 and the standard deviation is 15.

This means that \mu = 74, \sigma = 15

Question a:

Sample of 36 means that n = 36, s = \frac{15}{\sqrt{36}} = 2.5

This probability is 1 subtracted by the pvalue of Z when X = 78. So

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

By the Central Limit Theorem

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

Z = \frac{78 - 74}{2.5}

Z = 1.6

Z = 1.6 has a pvalue of 0.9452

1 - 0.9452 = 0.0548

0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

Question b:

Sample of 150 means that n = 150, s = \frac{15}{\sqrt{150}} = 1.2247

This probability is the pvalue of Z when X = 77 subtracted by the pvalue of Z when X = 71. So

X = 77

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

Z = \frac{77 - 74}{1.2274}

Z = 2.45

Z = 2.45 has a pvalue of 0.9929

X = 71

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

Z = \frac{71 - 74}{1.2274}

Z = -2.45

Z = -2.45 has a pvalue of 0.0071

0.9929 - 0.0071 = 0.9858

0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c. A random sample of size 219 yielding a sample mean of less than 74.2

Sample size of 219 means that n = 219, s = \frac{15}{\sqrt{219}} = 1.0136

This probability is the pvalue of Z when X = 74.2. So

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

Z = \frac{74.2 - 74}{1.0136}

Z = 0.2

Z = 0.2 has a pvalue of 0.5793

0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

5 0
3 years ago
5750 divided by 3.78
Tems11 [23]

Answer:

1521.16402

Step-by-step explanation:

use fraction- division format\frac{x}{y}

\frac{5750}{3.78}

Multiply the numerator and denominator by 100

\frac{575000}{378}

Reduce by 2

\frac{287500}{189}

Now do long division

          1521. 164022

189|287500

   -  189

        985

     -  945

           400

         - 378

              220

            - 189

                310

              - 189

                  1210

                - 1134

                     760

                   - 756

                          40

                         -  0

                           400

                         - 378

                              22

           

5 0
2 years ago
Read 2 more answers
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