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tankabanditka [31]
3 years ago
6

Can someone help me this is urgent I really apressuare if someone did this at time please

Mathematics
1 answer:
Mariulka [41]3 years ago
7 0
What's the question?

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Step-by-step explanation:

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In the figure above if PQRS is a square, what is the value of a?
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sino me quivoco es 1/53 espero aber ayudado

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How many 5-digit numbers can be formed using the digits 0, 1, 2, 3, 4, 5, 6, if repetition of digits is not allowed? a.119 b.16,
Sergeeva-Olga [200]
Answer:
c. 2520

Explanation:
Repetition is not allowed, therefore:
1st digit can be any of the given 7 numbers
2nd digit can be any of the remaining 6 numbers
3rd digit can be any of the remaining 5 numbers
4th digit can be any of the remaining 4 numbers
5th digit can be any of the remaining 3 numbers
This means that:
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Hope this helps :)
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PLEASE HELP!! WILL MARK BRAINLIEST AND HELP YOU!!!
bearhunter [10]

given: s is the midpoint of rt

definition of midpoint: rs st

given: st xg

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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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