Respuesta :
Answer:
[tex]z=1.28<\frac{a-239}{4.6}[/tex]
And if we solve for a we got
[tex]a=239 +1.28*4.6=244.89[/tex]
So the value of height that separates the bottom 90% of data from the top 10% is 244.89.
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".
Solution to the problem:
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:
[tex]X \sim N(239,23)[/tex]
Where [tex]\mu=239[/tex] and [tex]\sigma=23[/tex]
Since the distribution for X is normal then we know that the distribution for the sample mean [tex]\bar X[/tex] is given by:
[tex]\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})[/tex]
And we are interested on a value a such that:
[tex]P(\bar X>a)=0.10[/tex] (a)
[tex]P(\bar X<a)=0.90[/tex] (b)
Both conditions are equivalent on this case. We can use the z score again in order to find the value a.
As we can see on the figure attached the z value that satisfy the condition with 0.90 of the area on the left and 0.1 of the area on the right it's z=1.28. On this case P(Z<1.28)=0.9 and P(z>1.28)=0.1
If we use condition (b) from previous we have this:
[tex]P(\bar X<a)=P(\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n}}}<\frac{a-\mu}{\frac{\sigma}{\sqrt{n}}})=0.9[/tex]
[tex]P(z<\frac{a-\mu}{\frac{\sigma}{\sqrt{n}}})=0.9[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=1.28<\frac{a-239}{4.6}[/tex]
And if we solve for a we got
[tex]a=239 +1.28*4.6=244.89[/tex]
So the value of height that separates the bottom 90% of data from the top 10% is 244.89.