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Bezzdna [24]
3 years ago
6

Help due in 1o mins!!!

Mathematics
2 answers:
STatiana [176]3 years ago
7 0

Answer:

c = 15

Step-by-step explanation:

The angles are4 a linear pair and are supplementary, so the sum of their measures is 180 deg.

7c - 7 + 6c - 8 = 180

13c - 15 = 180

13c = 195

c = 15

suter [353]3 years ago
5 0
The answer should be 15.

Explanation:
The line equates to 180, so you would put both equations (7c-7 , 6c-8) together and equal it to 180°.
So, it would come out looking like this:
7c-7+6c-8=180.

You’d add 7c and 6c to get 13c, and then subtract -8 from -7 (-7-8) to get -15.
The equation would now look like this.
13c-15= 180.

You’d add 15 to 180 to get 195. Then, you’d divide 195 by 13 to get 15, which would mean c=15.
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Step-by-step explanation:

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A distribution of values is normal with a mean of 220 and a standard deviation of 13. From this distribution, you are drawing sa
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Answer:

The interval containing the middle-most 48% of sample means is between 218.59 to 221.41.

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 distributied random variable X, with mean \mu and standard deviation \sigma, the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 220, \sigma = 13, n = 35, s = \frac{13}{\sqrt{35}} = 2.1974

Find the interval containing the middle-most 48% of sample means:

50 - 48/2 = 26th percentile to 50 + 48/2 = 74th percentile. So

74th percentile

value of X when Z has a pvalue of 0.74. So X when Z = 0.643.

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

By the Central Limit Theorem

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

0.643 = \frac{X - 220}{2.1974}

X - 220 = 0.643*2.1974

X = 221.41

26th percentile

Value of X when Z has a pvalue of 0.26. So X when Z = -0.643

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

-0.643 = \frac{X - 220}{2.1974}

X - 220 = -0.643*2.1974

X = 218.59

The interval containing the middle-most 48% of sample means is between 218.59 to 221.41.

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