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Morgarella [4.7K]
3 years ago
14

Please help meeeeeeeeee im so confused

Mathematics
2 answers:
Alexeev081 [22]3 years ago
8 0
I believe C is the answer because of Keep Change Flip when you’re trying to multiply a fraction.
Snezhnost [94]3 years ago
4 0

Answer:

your right if you thin your wrong B can be right too

Step-by-step explanation:

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Solve the following dividend problem.alameda tent company has 75,000 shares of stock outstanding. what total dividend declaratio
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In a class of students, the following data table summarizes how many students have a brother or a sister. What is the probabilit
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22/29

Step-by-step explanation:

Idk

6 0
3 years ago
Find the sum of the first 56 terms of the sequence {-8,-1, 6, ...}.
torisob [31]

Answer:

Step-by-step explanation:

S56=56/2[2(-8)+(56-1)7]

S56=10332

4 0
3 years ago
In the library on a university campus, there is a sign in the elevator that indicates a limit of 16 persons. In addition, there
lesya692 [45]

Answer:

15.87% probability that a random sample of 16 people will exceed the weight limit

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.

For sums, the theorem can be applied, with mean n*\mu and standard deviation s = \sqrt{n}*\sigma

In this problem, we have that:

n = 16, \mu = 16*150 = 2400, s = \sqrt{16}*27 = 108

If a random sample of 16 persons from the campus is to be taken, what is the chance that a random sample of 16 people will exceed the weight limit

This is 1 subtracted by the pvalue of Z when X = 2508. So

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

By the Central Limit Theorem

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

Z = \frac{2508 - 2400}{108}

Z = 1

Z = 1 has a pvalue of 0.8413

1 - 0.8413 = 0.1587

15.87% probability that a random sample of 16 people will exceed the weight limit

3 0
3 years ago
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