The chosen topic is not meant for use with this type of problem. Try the examples below.
y = x+4
y = 2x-5
y = x-1
Hey!
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Steps To Solve:
4.6(x - 3) = -0.4x + 16.2
~Distributive property
4.6x - 13.8 = -0.4x + 16.2
~Add 0.4 to both sides
4.6x - 13.8 + 0.4= -0.4x + 16.2 + 0.4
~Simplify
5x - 13.8 = 16.2
~Add 13.8 to both sides
5x - 13.8 + 13.8 = 16.2 + 13.8
~Simplify
5x = 30
Divide 5 to both sides
5x/5 = 30/5
~Simplify
x = 6
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Answer:

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Hope This Helped! Good Luck!
X=6
16 plus 2 is 18 and divided by 3 is 6
Answer:
![g(x)=-2\sqrt[3]x](https://tex.z-dn.net/?f=g%28x%29%3D-2%5Csqrt%5B3%5Dx)
or

Step-by-step explanation:
Given
![f(x) = \sqrt[3]x](https://tex.z-dn.net/?f=f%28x%29%20%3D%20%5Csqrt%5B3%5Dx)
Required
Write a rule for g(x)
See attachment for grid
From the attachment, we have:


We can represent g(x) as:

So, we have:
![g(x) = n * \sqrt[3]x](https://tex.z-dn.net/?f=g%28x%29%20%3D%20n%20%2A%20%5Csqrt%5B3%5Dx)
For:

![2 = n * \sqrt[3]{-1}](https://tex.z-dn.net/?f=2%20%3D%20n%20%2A%20%5Csqrt%5B3%5D%7B-1%7D)
This gives:

Solve for n


To confirm this value of n, we make use of:

So, we have:
![-2 = n * \sqrt[3]1](https://tex.z-dn.net/?f=-2%20%3D%20n%20%2A%20%5Csqrt%5B3%5D1)
This gives:

Solve for n


Hence:
![g(x) = n * \sqrt[3]x](https://tex.z-dn.net/?f=g%28x%29%20%3D%20n%20%2A%20%5Csqrt%5B3%5Dx)
![g(x)=-2\sqrt[3]x](https://tex.z-dn.net/?f=g%28x%29%3D-2%5Csqrt%5B3%5Dx)
or:

Answer:
When sampling from a population, the sample mean will: be closer to the population mean as the sample size increases.
Step-by-step explanation:
The sample mean is not always equal to the population mean but if we increase the number of samples then the mean of the sample would become more and more closer to the population mean.
Usually the population size is very huge that is why we select a random sample from the population, care must be taken to ensure randomized sampling otherwise results would not be accurate. After that we have to make sure that the number of samples are enough for the given population size. The number of samples depends upon the shape of the population. If the population is normal than according to central limit theorem, a less number of samples would be enough to ensure normal distribution of sampling mean, otherwise a greater sample size will be required.