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Airida [17]
3 years ago
13

Given the figure below, find the values of

Mathematics
1 answer:
Burka [1]3 years ago
8 0
Https://tex.z-dn.net/?f=+%5Cfrac%7B8%7D%7B64%7D+%3D+%5Cfrac%7B2%7D%7Bx%7D++%5C%5C++%5C%5C+8x%3D128+%5C%5C++%5C%5C+x%3D16
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One number is 8 times another number. The numbers are both positive and have a difference of 70. Find the numbers.
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The answer is (b. 8x - x = 70).
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Need help on this question for math
KATRIN_1 [288]

Answer:

y=-7

Step-by-step explanation:

hope that will help you

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Which of these could be considered a statistical question?
MakcuM [25]

The statistical question would be B.

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We are going to sell Harlem Sweatshirts to raise money for
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32 sweatshirts

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3 years 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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