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Vikki [24]
3 years ago
15

PLEASE HELP ME ASAP?!?!

Mathematics
1 answer:
Vikentia [17]3 years ago
6 0

Answer:

b = 12

Step-by-step explanation:

Using the Pythagorean Theorem:

a² + b² = c²

You can identify that 12√12 is the hypotenuse, as it is opposite to the right angle.

So:

12² + b² = (12√2)²

144 + b² = [(12√2) (12√2)]

144 + b² = (12 × √2 × 12 × √2)

144 + b² = (144 × 2)

144 + b² = 288

b² = 144

√b² = √144

b = 12

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x² - 6x + 9

Step-by-step explanation:

(x - 3)² = x² - 6x + 9

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Write 3x-7+2(2x-7) as the product of 7 and another factor
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Answer:

7x - 3)

Step-by-step explanation:

Given

3x - 7 + 2(2x - 7) ← distribute parenthesis

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A flower surrounds the base of a tree. It is in close by stones to form a circle that measures 21.98 feet around. What is the ra
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(3.14)(21.98)(21.98)

-------------------------------

2

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2 years ago
The mean rent of a 3-bedroom apartment in Orlando is $1300. You randomly select 10 apartments around town. The rents are normall
lana [24]

Answer:

96.49% probability that the mean rent is more than $1100

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 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 problem, we have that:

\mu = 1300, \sigma = 350, n = 10, s = \frac{350}{\sqrt{10}} = 110.68

What is the probability that the mean rent is more than $1100?

This is 1 subtracted by the pvalue of Z when X = 1100. So

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

By the Central Limit Theorem

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

Z = \frac{1100 - 1300}{110.68}

Z = -1.81

Z = -1.81 has a pvalue of 0.0351

1 - 0.0351 = 0.9649

96.49% probability that the mean rent is more than $1100

7 0
3 years ago
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