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Volgvan
2 years ago
15

Which monomial is a perfect cube? 16x6 27x8 32x12 64x6

Mathematics
2 answers:
Marizza181 [45]2 years ago
7 0

Answer:  The answer is (D) 64x^6.

Step-by-step explanation:  We are to select the correct monomial from the given options which is a perfect cube.

The first option is

y=16x^6=2\times (8x^6)=2\times(2x^2)^3\\\\\Rightarrow \sqrt[3]{y}=2x^2\sqrt[3]{2}.

So, this is not a perfect cube.

The second option is

y=27x^8=x^2\times (27x^6)=x^2\times(3x^2)^3\\\\\Rightarrow \sqrt[3]{y}=3x^2\sqrt[3]{x^2}.

So, this is not a perfect cube.

The third option is

y=32x^{12}=4\times (8x^{12})=4\times(2x^4)^3\\\\\Rightarrow \sqrt[3]{y}=2x^4\sqrt[3]{4}.

So, this is not a perfect cube.

The fourth option is

y=64x^6=(4x^2)^3\\\\\Rightarrow \sqrt[3]{y}=4x^2.

So, this is a perfect cube.

Thus, (D) 64x^6 is the correct option.

Svetlanka [38]2 years ago
5 0
Which monomial is a perfect cube?<span>16x6</span><span>27x8</span><span>32x12</span><span>64x<span>6

Its D </span></span>
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11.51% probability that the mean annual salary of the sample is between $71000 and $73500

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}

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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 question, we have that:

\mu = 74000, \sigma = 2500, n = 36, s = \frac{2500}{\sqrt{36}} = 416.67

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This is the pvalue of Z when X = 73500 subtracted by the pvalue of Z when X = 71000. So

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

By the Central Limit Theorem

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

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

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0.1151 - 0 = 0.1151

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