Respuesta :
Answer:
a) [tex]P(58<X<80)=P(\frac{58-\mu}{\sigma}<\frac{X-\mu}{\sigma}<\frac{80-\mu}{\sigma})=P(\frac{58-63.4}{2.4}<Z<\frac{80-63.4}{2.4})=P(-2.25<z<6.917)[/tex]
And we can find this probability on this way:
[tex]P(-2.25<z<6.917)=P(z<6.917)-P(z<-2.25)[/tex]
And in order to find these probabilities we can use tables for the normal standard distribution, excel or a calculator.
[tex]P(-2.15<z<6.917)=P(z<6.917)-P(z<-2.15)=1-0.0158=0.984[/tex]
And that represent 98.4%
b) [tex]z=2.05<\frac{a-63.4}{2.4}[/tex]
And if we solve for a we got
[tex]a=63.4 +2.05*2.4=68.32[/tex]
So the value of height that separates the bottom 98% of data from the top 2% is 68.32.
[tex]z=-2.33<\frac{a-63.4}{2.4}[/tex]
And if we solve for a we got
[tex]a=63.4 -2.33*2.4=57.81[/tex]
So the value of height that separates the bottom 1% of data from the top 99% is 57.81.
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:
[tex]X \sim N(63.4,2.4)[/tex]
Where [tex]\mu=63.4[/tex] and [tex]\sigma=2.4[/tex]
We are interested on this probability
[tex]P(58<X<80)[/tex]
And the best way to solve this problem is using the normal standard distribution and the z score given by:
[tex]z=\frac{x-\mu}{\sigma}[/tex]
If we apply this formula to our probability we got this:
[tex]P(58<X<80)=P(\frac{58-\mu}{\sigma}<\frac{X-\mu}{\sigma}<\frac{80-\mu}{\sigma})=P(\frac{58-63.4}{2.4}<Z<\frac{80-63.4}{2.4})=P(-2.25<z<6.917)[/tex]
And we can find this probability on this way:
[tex]P(-2.25<z<6.917)=P(z<6.917)-P(z<-2.25)[/tex]
And in order to find these probabilities we can use tables for the normal standard distribution, excel or a calculator.
[tex]P(-2.15<z<6.917)=P(z<6.917)-P(z<-2.15)=1-0.0158=0.984[/tex]
And that represent 98.4%
Part b
For this part we want to find a value a, such that we satisfy this condition:
[tex]P(X>a)=0.02[/tex] (a)
[tex]P(X<a)=0.98[/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 0.98 of the area on the left and 0.02 of the area on the right it's z=2.05. On this case P(Z<2.05)=0.98 and P(z>2.05)=0.02
If we use condition (b) from previous we have this:
[tex]P(X<a)=P(\frac{X-\mu}{\sigma}<\frac{a-\mu}{\sigma})=0.98[/tex]
[tex]P(z<\frac{a-\mu}{\sigma})=0.98[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=2.05<\frac{a-63.4}{2.4}[/tex]
And if we solve for a we got
[tex]a=63.4 +2.05*2.4=68.32[/tex]
So the value of height that separates the bottom 98% of data from the top 2% is 68.32.
For the other value we need
[tex]P(X>a)=0.99[/tex] (a)
[tex]P(X<a)=0.01[/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 0.01 of the area on the left and 0.99 of the area on the right it's z=-2.33. On this case P(Z<-2.33)=0.01 and P(z>-2.33)=0.99
If we use condition (b) from previous we have this:
[tex]P(X<a)=P(\frac{X-\mu}{\sigma}<\frac{a-\mu}{\sigma})=0.01[/tex]
[tex]P(z<\frac{a-\mu}{\sigma})=0.01[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=-2.33<\frac{a-63.4}{2.4}[/tex]
And if we solve for a we got
[tex]a=63.4 -2.33*2.4=57.81[/tex]
So the value of height that separates the bottom 1% of data from the top 99% is 57.81.
Correct Answer: 98.78
A. 98. 78
A) Part 2: No, because only a small percentage of women are not allowed to join this branch of the military because of their height.
B. 57.8 , 68.3