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san4es73 [151]
2 years ago
12

Can someone please help? Thanks!

Mathematics
1 answer:
Paul [167]2 years ago
7 0

Hey, I have already answered these all questions except the last question in your previous question. Make sure to see them.

For the last question, the answer would be the second choice as when times keep flowing, the distance still remains the same (not to be confused with speed.)

Basically when times keep going, the distance will stay the same without any changes.

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Where is the picture for the problem?
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Subject: Finding Range Using a Graph
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4.7

Step-by-step explanation:

The red I think is hinting to the x.

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Please help<br><br> isolate x in <br> x+3y=1
Evgesh-ka [11]
Subtract 3y and move it to the right
X= 1 - 3Y
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Read 2 more answers
John manages 27 apple orchards in North Georgia. He wants to split the orchards into thirds so that he can open 3 local stores.
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Answer: 27 x 1/3

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1 year ago
An Epson inkjet printer ad advertises that the black ink cartridge will provide enough ink for an average of 245 pages. Assume t
Neko [114]

Answer:

35.2% probability that the sample mean will be 246 pages or more

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 question, we have that:

\mu = 245 \sigma = 15, n = 33, s = \frac{15}{\sqrt{33}} = 2.61

What the probability that the sample mean will be 246 pages or more?

This is 1 subtracted by the pvalue of Z when X = 246. So

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

By the Central Limit Theorem

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

Z = \frac{246 - 245}{2.61}

Z = 0.38

Z = 0.38 has a pvalue of 0.6480.

1 - 0.6480 = 0.3520

35.2% probability that the sample mean will be 246 pages or more

4 0
3 years ago
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