Respuesta :
Answer:
a) [tex]P(X>25)=P(\frac{X-\mu}{\sigma}>\frac{25-\mu}{\sigma})=P(Z>\frac{25-22}{2})=P(z>1.5)[/tex]
And we can find this probability using the complement rule and we got:
[tex]P(z>1.5)=1-P(z<1.5)=1-0.933193=0.06681 [/tex]
b) [tex]z=0.332<\frac{a-22}{2}[/tex]
And if we solve for a we got
[tex]a=22 +0.332*2=22.664[/tex]
So the value of height that separates the bottom 63% of data from the top 37% is 22.664.
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 scores of a population, and for this case we know the distribution for X is given by:
[tex]X \sim N(22,2)[/tex]
Where [tex]\mu=22[/tex] and [tex]\sigma=2[/tex]
We are interested on this probability
[tex]P(X>25)[/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(X>25)=P(\frac{X-\mu}{\sigma}>\frac{25-\mu}{\sigma})=P(Z>\frac{25-22}{2})=P(z>1.5)[/tex]
And we can find this probability using the complement rule and we got:
[tex]P(z>1.5)=1-P(z<1.5)=1-0.933193=0.06681 [/tex]
Part b
For this part we want to find a value a, such that we satisfy this condition:
[tex]P(X>a)=0.37[/tex] (a)
[tex]P(X<a)=0.63[/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 0.63 of the area on the left and 0.37 of the area on the right it's z=0.332. On this case P(Z<0.332)=0.63 and P(z>0.332)=0.37
If we use condition (b) from previous we have this:
[tex]P(X<a)=P(\frac{X-\mu}{\sigma}<\frac{a-\mu}{\sigma})=0.63[/tex]
[tex]P(z<\frac{a-\mu}{\sigma})=0.63[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=0.332<\frac{a-22}{2}[/tex]
And if we solve for a we got
[tex]a=22 +0.332*2=22.664[/tex]
So the value of height that separates the bottom 63% of data from the top 37% is 22.664.