Which of the following expressions represents the statement below?

Len [333]

Answer:

?????????????????????????????????

4 0

3 years ago

The daily cost of hiring an electrician,Y, to work x hours on an electric job can be modeled using a linear function. The electr

Artyom0805 [142]

B is the answer to your question

4 0

3 years ago

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HELPPPPPPPP T^T I NEED AN ANSWER!!!! IS THE QUESATIN A OR C

KonstantinChe [14]

Answer:

Commutative

Please, mark as brainliest

5 0

3 years ago

The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 500 psi. (a) What is the probability

velikii [3]

Answer:

a) 89.05% probability that the sample mean breaking strength for a random sample of 40 rivets is between 9900 and 10,200

b) No, because one of the requirements of the central limit theorem is a sample size of at least 30.

Step-by-step explanation:

To solve this question, we have 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 $\sigma$ , the sample means with size n 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:

$\mu = 10000, \sigma = 500$

(a) What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9900 and 10,200?

Here we have $n = 40, s = \frac{500}{\sqrt{40}} = 79.06$

This probability is the pvalue of Z when X = 10200 subtracted by the pvalue of Z when X = 9900. So

X = 10200

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

By the Central Limit Theorem

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

$Z = \frac{10200 - 10000}{79.06}$

$Z = 2.53$

$Z = 2.53$ has a pvalue of 0.9943.

X = 9900

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

$Z = \frac{9900 - 10000}{79.06}$

$Z = -1.26$

$Z = -1.26$ has a pvalue of 0.1038.

0.9943 - 0.1038 = 0.8905

89.05% probability that the sample mean breaking strength for a random sample of 40 rivets is between 9900 and 10,200

(b) If the sample size had been 15 rather than 40, could the probability requested in part (a) be calculated from the given information?

No, because one of the requirements of the central limit theorem is a sample size of at least 30.

3 0

3 years ago

From two-dimensional space to three dimensional space, the number of quadrants ___________

FromTheMoon [43]

Answer:

<h2>Increase.</h2>

Step-by-step explanation:

Two-dimensional space is modelled by the coordiante system with 4 quadrants only, and the axis are x and y, the independent and the dependent variables, respectively.

On the other hand, the three-dimensional space has three coordinates, x, y and z. The extra coordinate allows to have a three-dimensional space. Also, this extra coordinate increases the number of quadrants, actually, they are called octants, becayse they are eight.

Therefore, the word missing here is "increase".

4 0

4 years ago

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