Respuesta :
Answer:
i) [tex] P(9.5 < X<11)[/tex]
And we can solve this problem using 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(9.5<X<11)=P(\frac{9.5-\mu}{\sigma}<\frac{X-\mu}{\sigma}<\frac{11-\mu}{\sigma})=P(\frac{9.5-10}{1.414}<Z<\frac{11-10}{1.414})=P(-0.354<z<0.707)[/tex]
And we can find this probability with this difference:
[tex]P(-0.354<z<0.707)=P(z<0.707)-P(z<-0.354)[/tex]
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
[tex]P(-0.354<z<0.707)=P(z<0.707)-P(z<-0.354)=0.7602-0.3617=0.3985[/tex]
ii) The z scores for this case are:
[tex] z_1 = \frac{9.5-10}{1.414}= -0.354[/tex]
[tex] z_2 = \frac{11-10}{1.414}= 0.707[/tex]
And we can check the answer with the following excel code:
=NORM.DIST(0.707,0,1,TRUE)-NORM.DIST(-0.354,0,1,TRUE)
iii) [tex]P(X>a)=0.975[/tex] (a)
[tex]P(X<a)=0.025[/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 0.025 of the area on the left and 0.975 of the area on the right it's z=-1.96. On this case P(Z<-1.96)=0.025 and P(z>-1.96)=0.975
If we use condition (b) from previous we have this:
[tex]P(X<a)=P(\frac{X-\mu}{\sigma}<\frac{a-\mu}{\sigma})=0.975[/tex]
[tex]P(z<\frac{a-\mu}{\sigma})=0.975[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=-1.96<\frac{a-10}{1.414}[/tex]
And if we solve for a we got
[tex]a=10 -1.96*1.414=7.228[/tex]
So the value of height that separates the bottom 2.5% of data from the top 97.5% is 7.228.
iv) [tex] z = \frac{7.228-10}{1.414}= -1.96[/tex]
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 blade length of a population, and for this case we know the distribution for X is given by:
[tex]X \sim N(10,\sqrt{2})[/tex]
Where [tex]\mu=10[/tex] and [tex]\sigma=1.414[/tex]
Part i
For this case we want this probability:
[tex] P(9.5 < X<11)[/tex]
And we can solve this problem using 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(9.5<X<11)=P(\frac{9.5-\mu}{\sigma}<\frac{X-\mu}{\sigma}<\frac{11-\mu}{\sigma})=P(\frac{9.5-10}{1.414}<Z<\frac{11-10}{1.414})=P(-0.354<z<0.707)[/tex]
And we can find this probability with this difference:
[tex]P(-0.354<z<0.707)=P(z<0.707)-P(z<-0.354)[/tex]
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
[tex]P(-0.354<z<0.707)=P(z<0.707)-P(z<-0.354)=0.7602-0.3617=0.3985[/tex]
Part ii
The z scores for this case are:
[tex] z_1 = \frac{9.5-10}{1.414}= -0.354[/tex]
[tex] z_2 = \frac{11-10}{1.414}= 0.707[/tex]
And we can check the answer with the following excel code:
=NORM.DIST(0.707,0,1,TRUE)-NORM.DIST(-0.354,0,1,TRUE)
Part iii
For this part we want to find a value a, such that we satisfy this condition:
[tex]P(X>a)=0.975[/tex] (a)
[tex]P(X<a)=0.025[/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 0.025 of the area on the left and 0.975 of the area on the right it's z=-1.96. On this case P(Z<-1.96)=0.025 and P(z>-1.96)=0.975
If we use condition (b) from previous we have this:
[tex]P(X<a)=P(\frac{X-\mu}{\sigma}<\frac{a-\mu}{\sigma})=0.975[/tex]
[tex]P(z<\frac{a-\mu}{\sigma})=0.975[/tex]
But we know which value of z satisfy the previous equation so then we can do this:
[tex]z=-1.96<\frac{a-10}{1.414}[/tex]
And if we solve for a we got
[tex]a=10 -1.96*1.414=7.228[/tex]
So the value of height that separates the bottom 2.5% of data from the top 97.5% is 7.228.
Part iv
The z score for this value is given by:
[tex] z = \frac{7.228-10}{1.414}= -1.96[/tex]