Respuesta :
Answer:
a) [tex] x = \mu +z*\sigma[/tex]
And replacing we got:
[tex] x= 2.98 + 1.71*0.36 = 3.5956[/tex]
b) [tex] x = \mu +z*\sigma[/tex]
And replacing we got:
[tex] x= 21.6 + 1.18*7.1 = 29.978[/tex]
c) [tex] x = \mu -z*\sigma[/tex]
And replacing we got:
[tex] x= 150 - 1.35*40= 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".
Part a
Let X the random variable of interest for this case. We define the z score with the following formula:
[tex]z=\frac{x-\mu}{\sigma}[/tex]
And for this case we know that [tex] z = 1.71, \mu = 2.98,\sigma = 0.36[/tex]
If we solve for x from the z score formula we got:
[tex] x = \mu +z*\sigma[/tex]
And replacing we got:
[tex] x= 2.98 + 1.71*0.36 = 3.5956[/tex]
Part b
Let X the random variable of interest for this case. We define the z score with the following formula:
[tex]z=\frac{x-\mu}{\sigma}[/tex]
And for this case we know that [tex] z = 1.18, \mu = 21.6,\sigma = 7.1[/tex]
If we solve for x from the z score formula we got:
[tex] x = \mu +z*\sigma[/tex]
And replacing we got:
[tex] x= 21.6 + 1.18*7.1 = 29.978[/tex]
Part c
Let X the random variable of interest for this case. We define the z score with the following formula:
[tex]z=\frac{x-\mu}{\sigma}[/tex]
And for this case we know that [tex] z = -1.35, \mu = 150,\sigma = 40[/tex]
If we solve for x from the z score formula we got:
[tex] x = \mu -z*\sigma[/tex]
And replacing we got:
[tex] x= 150 - 1.35*40= 96[/tex]