Answer:
a) ![P(\bar X](https://tex.z-dn.net/?f=P%28%5Cbar%20X%3C90%29%3DP%28Z%3C%5Cfrac%7B90-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28Z%3C-2.03%29%3D%200.0212)
b)![P(98](https://tex.z-dn.net/?f=P%2898%3C%5Cbar%20X%3C105%29%3DP%28-0.39%3CZ%3C1.05%29%3DP%28Z%3C1.05%29-P%28Z%3C-0.39%29%3D0.8531-0.3483%3D0.5049)
c) ![P(\bar X](https://tex.z-dn.net/?f=P%28%5Cbar%20X%3C112%29%3DP%28Z%3C%5Cfrac%7B112-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28Z%3C2.49%29%3D%200.9936)
d) ![P(93](https://tex.z-dn.net/?f=P%2893%3C%5Cbar%20X%3C96%29%3DP%28-1.42%3CZ%3C-0.80%29%3DP%28Z%3C-0.80%29-P%28Z%3C-1.42%29%3D0.2119-0.0778%3D0.1341)
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Part a
Let X the random variable that represent the heights of a population, and for this case we know the distribution for X is given by:
Where
and ![\sigma=30](https://tex.z-dn.net/?f=%5Csigma%3D30)
We select a random sample of n=36. And from the central limit theorem we know that the distribution for the sample is given by:
![\bar X \sim N(\mu =99.9 , \frac{\sigma}{\sqrt{n}}= \frac{30}{\sqrt{38}}=4.87)](https://tex.z-dn.net/?f=%5Cbar%20X%20%5Csim%20N%28%5Cmu%20%3D99.9%20%2C%20%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%3D%20%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%3D4.87%29)
And the best way to solve this problem is using the normal standard distribution and the z score given by:
![z=\frac{x-\mu}{\frac{\sigma}{\sqrt{n}}}](https://tex.z-dn.net/?f=z%3D%5Cfrac%7Bx-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D)
If we apply this formula to our probability we got this:
![P(\bar X](https://tex.z-dn.net/?f=P%28%5Cbar%20X%3C90%29%3DP%28%5Cfrac%7BX-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7B90-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29)
![=P(Z](https://tex.z-dn.net/?f=%3DP%28Z%3C%5Cfrac%7B90-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28Z%3C-2.03%29%3D%200.0212)
Part b
For this case we want this probability:
![P(98](https://tex.z-dn.net/?f=P%2898%3C%5Cbar%20X%3C105%29%3DP%28%5Cfrac%7B98-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7BX-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7B105-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%29)
![=P(\frac{98-99.9}{\frac{30}{\sqrt{38}}}](https://tex.z-dn.net/?f=%3DP%28%5Cfrac%7B98-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%3CZ%3C%5Cfrac%7B105-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28-0.39%3CZ%3C1.05%29)
And we can find this probability on this way:
![P(-0.39](https://tex.z-dn.net/?f=P%28-0.39%3CZ%3C1.05%29%3DP%28Z%3C1.05%29-P%28Z%3C-0.39%29)
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
![P(-0.39](https://tex.z-dn.net/?f=P%28-0.39%3CZ%3C1.05%29%3DP%28Z%3C1.05%29-P%28Z%3C-0.39%29%3D0.8531-0.3483%3D0.5049)
Part c
If we apply this formula to our probability we got this:
![P(\bar X](https://tex.z-dn.net/?f=P%28%5Cbar%20X%3C112%29%3DP%28%5Cfrac%7BX-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7B112-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29)
![P(\bar X](https://tex.z-dn.net/?f=P%28%5Cbar%20X%3C112%29%3DP%28Z%3C%5Cfrac%7B112-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28Z%3C2.49%29%3D%200.9936)
Part d
For this case we want this probability:
![P(93](https://tex.z-dn.net/?f=P%2893%3C%5Cbar%20X%3C96%29%3DP%28%5Cfrac%7B93-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7BX-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3C%5Cfrac%7B96-%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%29)
![=P(\frac{93-99.9}{\frac{30}{\sqrt{38}}}](https://tex.z-dn.net/?f=%3DP%28%5Cfrac%7B93-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%3CZ%3C%5Cfrac%7B96-99.9%7D%7B%5Cfrac%7B30%7D%7B%5Csqrt%7B38%7D%7D%7D%29%3DP%28-1.42%3CZ%3C-0.80%29)
And we can find this probability on this way:
![P(-1.42](https://tex.z-dn.net/?f=P%28-1.42%3CZ%3C-0.80%29%3DP%28Z%3C-0.80%29-P%28Z%3C-1.42%29)
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
![P(-1.42](https://tex.z-dn.net/?f=P%28-1.42%3CZ%3C-0.80%29%3DP%28Z%3C-0.80%29-P%28Z%3C-1.42%29%3D0.2119-0.0778%3D0.1341)