Answer:
[tex] z= \frac{0.6-0.637}{0.0439} =-0.843[/tex]
So then we can find the probability like this:
[tex]P(p<0.6) = P(Z<-0.843)[/tex]
And using the normal standard table or excel we got:
[tex]P(p<0.6) = P(Z<-0.843)=0.1996[/tex]
Step-by-step explanation:
For this case we can check if we can use the normal approximation for the proportion and we have this:
[tex] np = 120*0.637 =76.44 >10[/tex]
[tex] n(1-p) = 120*(1-0.637) = 43.56>10[/tex]
Then we can conclude that we can use the normal approximation. And we have this:
[tex] p\sim N (p, \sqrt{\frac{p(1-p)}{n}})[/tex]
So the mean is given by:
[tex]\mu_p = 0.637[/tex]
And the deviation is given by:
[tex]\sigma_p = \sqrt{\frac{0.637*(1-0.637)}{120}}= 0.0439[/tex]
And for this case we want to find this probability:
[tex] P( p<0.6)[/tex]
And we can use the z score given by:
[tex] z = \frac{p -\mu}{\sigma_p}[/tex]
And for this case the z score is:
[tex] z= \frac{0.6-0.637}{0.0439} =-0.843[/tex]
So then we can find the probability like this:
[tex]P(p<0.6) = P(Z<-0.843)[/tex]
And using the normal standard table or excel we got:
[tex]P(p<0.6) = P(Z<-0.843)=0.1996[/tex]