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Triss [41]
3 years ago
11

John plans to practice piano at least 2 1 2 212 hours this weekend. If he practices 1 1 6 116 hours on Saturday and 1 1 4 114 ho

urs on Sunday, will he meet his goal?
A. Yes; he will practice a total of 2 5/12 hours, and 2 5/12 > 2 1/2.


B. No; he will practice a total of 2 5/12 hours, and 2 7/12 < 2 1/2


C. Yes; he will practice a total of 2 7/12 hours, and 2 7/12 < 2 1/2


D. No; he will practice a total of 2 7/12 hours, and 2 7/12 < 2 1/2
Mathematics
1 answer:
Irina18 [472]3 years ago
7 0
Kigyunbrjnhbbhncbnuybnmk
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23.535 = 23 353/1000 = 23 107/200
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How do you Solve <br><br> 24=6(-x-3)
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You use the distributive prop. Then you add 18 to both sides and you get your answer.
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Answer:

Step-by-step explanation:

Angles 3, 4, and 5 are supplementary to each other, meaning that all of them added together equal 180.  Therefore, to solve for x:

x + 18 + x + 15 + 4x + 3 = 180 and

6x + 36 = 180 and

6x = 144 so

x = 24

Angles 1 and 3 are vertical angles, so they are congruent, meaning they both have the exact same angle measure.  If angle 3 measures, x + 18, so does angle 1.  If x = 24, then angle 1 = 24 + 18 which is 42 degrees.

That also answered part c.  Angles 1 and 3 are not complementary, they are vertical.

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Juries should have the same racial distribution as the surrounding communities. According to the U.S. Census Bureau, 18% of resi
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Answer:

0.997 = 99.7% probability that the resulting sample proportion to be between 0.066 and 0.294

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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

18% of residents in Minneapolis, Minnesota, are African Americans. Suppose a local court will randomly sample 100 state residents and will then observe the proportion in the sample who are African American.

This means that p = 0.18, n = 100

So, by the Central Limit Theorem:

\mu = 0.18, s = \sqrt{\frac{0.18*0.82}{100}} = 0.0384

How likely is the resulting sample proportion to be between 0.066 and 0.294?

This is the pvalue of Z when X = 0.294 subtracted by the pvalue of Z when X = 0.066. So

X = 0.294

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

Z = \frac{0.066 - 0.18}{0.0384}

Z = -2.97

Z = -2.97 has a pvalue of 0.0015

0.9985 - 0.0015 = 0.997

0.997 = 99.7% probability that the resulting sample proportion to be between 0.066 and 0.294

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