Respuesta :
Answer:
a) [tex]P(X<18.1)=P(\frac{X-\mu}{\sigma}<\frac{18.1-\mu}{\sigma})=P(Z<\frac{18.1-26.3}{5.4})=P(Z<-1.519)[/tex]
And we can find this probability using the normal standard table or excel and we got:
[tex]P(Z<-1.519)=0.0644[/tex]
That correspond to approximate 6.44%
b) [tex]P(X>31)=P(\frac{X-\mu}{\sigma}>\frac{31-\mu}{\sigma})=P(Z>\frac{31-26.3}{5.4})=P(Z>0.87)[/tex]
And we can find this probability using the normal standard table or excel and we got:
[tex]P(Z>0.87)=1-P(Z<0.87)= 1-0.808=0.192[/tex]
That correspond to approximate 19.2%
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 BMI of a population, and for this case we know the distribution for X is given by:
[tex]X \sim N(26.3,5.4)[/tex]
Where [tex]\mu=26.3[/tex] and [tex]\sigma=5.4[/tex]
We are interested on this probability
[tex]P(X<18.1)[/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<18.1)=P(\frac{X-\mu}{\sigma}<\frac{18.1-\mu}{\sigma})=P(Z<\frac{18.1-26.3}{5.4})=P(Z<-1.519)[/tex]
And we can find this probability using the normal standard table or excel and we got:
[tex]P(Z<-1.519)=0.0644[/tex]
That correspond to approximate 6.44%
Part b
We are interested on this probability
[tex]P(X>31)[/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>31)=P(\frac{X-\mu}{\sigma}>\frac{31-\mu}{\sigma})=P(Z>\frac{31-26.3}{5.4})=P(Z>0.87)[/tex]
And we can find this probability using the normal standard table or excel and we got:
[tex]P(Z>0.87)=1-P(Z<0.87)= 1-0.808=0.192[/tex]
That correspond to approximate 19.2%
(a) The percentage of young men are underweight is "13.14%".
(b) The percentage of young men are obese is "33.36%".
Given that,
Underweight,
- [tex]\mu = 26.8[/tex]
- [tex]\sigma = 7.4[/tex]
(a)
The underweight probability will be:
→ [tex]P(x < 18.5) = P(X< \frac{(18.5-26.8)}{7.4} )[/tex]
[tex]= P(Z < -1.12)[/tex]
[tex]= 0.1314[/tex]
[tex]= 13.14[/tex] (%)
(b)
The obese probability will be:
→ [tex]P(x> 30) = P(Z> \frac{(30-26.8)}{7.4} )[/tex]
[tex]= P(Z > 0.43)[/tex]
[tex]= 0.3336[/tex]
[tex]= 33.36[/tex] (%)
Thus the responses above are correct.
Learn more about statistics here:
https://brainly.com/question/22971642