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Tresset [83]
3 years ago
13

Write the number. 298 thousand, 216

Mathematics
2 answers:
abruzzese [7]3 years ago
6 0

Hey there!

Answer: \boxed{298,216}

Explanation:

Let's write 298 thousand 216 in standard form. Thousands have 3 zero's. Let's add 3 zero's for 298.

298,000

Now let's go to 216. 215 is already in standard. Now let's combine it.

\boxed{298,216} \text{ is your answer.}

Hope this helps!

\text{-TestedHyperr}

NeX [460]3 years ago
3 0

Answer:

298216

Step-by-step explanation:

i think youre talking about both of them as the same number? instead of 298000, 216 but i did my best to understand it. :)

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I got -4 but I don't see it on here, did I do something wrong??​
Ira Lisetskai [31]

Answer:

it is -4

Step-by-step explanation:

but the answer is not on there so the answer will be D.

5 0
2 years ago
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The mean rent of a 3-bedroom apartment in Orlando is $1300. You randomly select 10 apartments around town. The rents are normall
lana [24]

Answer:

96.49% probability that the mean rent is more than $1100

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 problem, we have that:

\mu = 1300, \sigma = 350, n = 10, s = \frac{350}{\sqrt{10}} = 110.68

What is the probability that the mean rent is more than $1100?

This is 1 subtracted by the pvalue of Z when X = 1100. So

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

By the Central Limit Theorem

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

Z = \frac{1100 - 1300}{110.68}

Z = -1.81

Z = -1.81 has a pvalue of 0.0351

1 - 0.0351 = 0.9649

96.49% probability that the mean rent is more than $1100

7 0
4 years ago
The graph of y=1/x is shown below. Draw the graph of its inverse.
lord [1]
Y=1/x  solve for x

x=1/y  now reverse lables...

y=1/x  

Yes that is the same equation you started with.  What that means is the the inverse function in this case produces the same exact graph :)
4 0
4 years ago
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Steven paid 15% down on a car. His down payment was $2,100. How much does he still owe on the car?
My name is Ann [436]

Answer:

315

Step-by-step explanation:

because 15% of 2,100 is 315

3 0
3 years ago
The answer of this question
Furkat [3]

Answer:

A≈380.13m² so B

Step-by-step explanation:

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Hope This Helps!       Have A Nice Day!!

3 0
3 years ago
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