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Ber [7]
3 years ago
11

Calculate the perimiter of a regular pentagon with side length of 5 cm

Mathematics
1 answer:
avanturin [10]3 years ago
8 0

Answer:

Regular pentagon

Solve for perimeter

P=25cm

a Side

5

cm

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Last year the depth of the river was 4.2 feet deep.
erastova [34]

Answer:

3.864

Step-by-step explanation:

convert 8% to decimal, you get .08

multiply that by 4.2 and you get 0.336, which means that 0.336 is 8% of 4.2

subtract 0.336 from 4.2

3.864

4 0
3 years ago
Suppose data made available through a health system tracker showed health expenditures were $10,348 per person in the United Sta
nignag [31]

Answer:

a) 30.08% probability the sample mean will be within $100 of the population mean.

b) 0% probability the sample mean will be greater than $12,600

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the Central Limit Theorem.

Normal probability distribution

When the distribution is normal, we use 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 question, we have that:

\mu = 10348, \sigma = 2500, n = 100, s = \frac{2500}{\sqrt{100}} = 250

a. What is the probability the sample mean will be within ±$100 of the population mean?

This is the pvalue of Z when X = 100 divided by s subtracted by the pvalue of Z when X = -100 divided by s. So

Z = \frac{100}{250} = 0.4

Z = -\frac{100}{250} = -0.4

Z = 0.4 has a pvalue of 0.6554, Z = -0.4 has a pvalue of 0.3556

0.6554 - 0.3546 = 0.3008

30.08% probability the sample mean will be within $100 of the population mean.

b. What is the probability the sample mean will be greater than $12,600?

This is 1 subtracted by the pvalue of Z when X = 12600. So

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

By the Central Limit Theorem

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

Z = \frac{12600 - 10348}{250}

Z = 9

Z = 9 has a pvalue of 1.

1 - 1 = 0

0% probability the sample mean will be greater than $12,600

5 0
3 years ago
Convert these sums into decimal.
alex41 [277]
A) 0.6
b) 0.65
c) 0.104
d) 0.32
7 0
3 years ago
Which golfer had the lowest number of strokes per hole?
ozzi
You have to post a picture
3 0
3 years ago
Please answer quick.​
Irina18 [472]

Answer:

3. 42

4. 38.7

Step-by-step explanation:

5 0
3 years ago
Read 2 more answers
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