I need help? Can somebody explain to me what you do here and give me the answer? Please and Thank You

Mathematics

1 answer:

rjkz [21]3 years ago

7 0

Answer:

you just locate where those fractions, decimals and percentage are located..

it's better if you turn them into decimal so it's easier to locate..

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The living room in the house has an area off 244 square feet and a width of 14 feet what is the length of the room

xxTIMURxx [149]

Answer:

Step-by-step explanation:

So if its 224 square feet and the width if 14 feet the length should be 14 also I think lol Here , imagine a square put 224 inside it for the area , then put down 14 on top and bottom because its the width , multiple 14×14=56+140=196+14=210+14=224 And the last 14's are the length which u have to add Im not sure if that made any sence lol but I hope it did .

7 0

2 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

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