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scoundrel [369]
3 years ago
7

What is the cube root of 25​

Mathematics
2 answers:
Neko [114]3 years ago
7 0

Answer:

15625

Your welcome. Have a great day :D

yanalaym [24]3 years ago
3 0

Answer:

2.9

Step-by-step explanation:

and yw i saw that u put thx in the comments

You might be interested in
The expression 6+16k factored using the GCF is what???????
tatiyna

Answer:

2(3 + 8k)

Step-by-step explanation:

given : 6+16k

note that the GCF of 6 and 16 is 2, hence we can factor 2 out of the expression

6+16k

= (2)(3) + (2)(8k)

= 2(3 + 8k)

4 0
3 years ago
The time a randomly selected individual waits for an elevator in an office building has a uniform distribution with a mean of 0.
Amiraneli [1.4K]

Answer:

The mean of the sampling distribution of means for SRS of size 50 is \mu = 0.5 and the standard deviation is s = 0.0409

By the Central Limit Theorem, since we have of sample of 50, which is larger than 30, it does not matter that the underlying population distribution is not normal.

0% probability a sample of 50 people will wait longer than 45 seconds for an elevator.

Step-by-step explanation:

To solve this problem, 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 random variable X, with mean \mu and standard deviation \sigma, a large sample size, of at least 30, can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 0.5, \sigma = 0.289

What are the mean and standard deviation of the sampling distribution of means for SRS of size 50?

By the Central Limit Theorem

\mu = 0.5, s = \frac{0.289}{\sqrt{50}} = 0.0409

The mean of the sampling distribution of means for SRS of size 50 is \mu = 0.5 and the standard deviation is s = 0.0409

Does it matter that the underlying population distribution is not normal?

By the Central Limit Theorem, since we have of sample of 50, which is larger than 30, it does not matter that the underlying population distribution is not normal.

What is the probability a sample of 50 people will wait longer than 45 seconds for an elevator?

We have to use 45 seconds as minutes, since the mean and the standard deviation are in minutes.

Each minute has 60 seconds.

So 45 seconds is 45/60 = 0.75 min.

This probability is 1 subtracted by the pvalue of Z when X = 0.75. So

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

By the Central Limit Theorem

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

Z = \frac{0.75 - 0.5}{0.0409}

Z = 6.11

Z = 6.11 has a pvalue of 1

1-1 = 0

0% probability a sample of 50 people will wait longer than 45 seconds for an elevator.

8 0
3 years ago
The sum of a number and 9, times 12
Sliva [168]

Answer:

1 + 9 x 12 = 120

2 + 9 x 12 = 132

3 + 9 x 12 = 144

4 + 9 x 12 = 156

5 + 9 x 12 = 168

Step-by-step explanation:

Any of the ones on top, but there are tons of others too

6 0
3 years ago
Please answer this question fast
Sphinxa [80]

Answer:

I think it is 6(5/6)

6 0
3 years ago
HELP PLEASE!!
Verizon [17]

did you ever get the answer?

4 0
3 years ago
Read 2 more answers
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