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Yuliya22 [10]
3 years ago
15

All of these value from smallest to largest

Mathematics
1 answer:
ollegr [7]3 years ago
3 0
You didn't put the values..??
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What is the perimeter of a rectangle with length of √18 and width of √8 in simplest form?
EastWind [94]

Answer:

P=10√2

Step-by-step explanation:

Perimeter of rectangle= 2 length + 2 width

P=2l+2w

P=2(√18)+2(√8)

P=2(√9*2)+2(√4*2)

P=2*3*√2 +2*2√2

P=6√2+4√2

P=10√2

4 0
3 years ago
Which ordered pair satisfies the equation y =(-5)? A.(-6,1) B. (-2,7) C.(2,-7) D.(-1,-6)​
frutty [35]

um i think it's a. don't quote me on it tho

6 0
3 years ago
Drag each number to the correct location in the ordered pairs. Each number can be used more than once, but not all numbers will
marishachu [46]

Answer:what?

Step-by-step explanation:

4 0
3 years ago
A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The s
Fofino [41]

Answer:

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

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}}

In this question, we have that:

\mu = 270, \sigma = 90, n = 18, s = \frac{90}{\sqrt{18}} = 21.2

What is the probability that 18 randomly selected bulbs would have an average life of no more than 260 days?

This is the pvalue of Z when X = 260. So

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

By the Central Limit Theorem

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

Z = \frac{260 - 270}{21.2}

Z = -0.47

Z = -0.47 has a pvalue of 0.3192.

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

5 0
3 years ago
the length and width of a rectangle are 4 feet and 3 feet, respectively. a similar rectangle has a width of 9 feet. what is the
icang [17]

Answer:

4 times 3 similar is 9 it could be something times 9 for the second.

8 0
3 years ago
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