Respuesta :
Answer:
As 0.17 is below the upper limit of the confidence interval, so we can conclude that the population proportion is less than 0.17.
Step-by-step explanation:
We are given that a survey of 270 young professionals found that one dash eighth of them use their cell phones primarily for e-mail.
Firstly, the Pivotal quantity for 95% confidence interval for the population proportion is given by;
P.Q. = [tex]\frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] ~ N(0,1)
where, [tex]\hat p[/tex] = sample proportion of people who use their cell phones primarily for e-mail = [tex]\frac{1}{8}[/tex] = 0.125
n = sample of young professionals = 270
p = population proportion
Here for constructing 95% confidence interval we have used One-sample z test for proportions.
So, 95% confidence interval for the population proportion, p is ;
P(-1.96 < N(0,1) < 1.96) = 0.95 {As the critical value of z at 2.5% level
of significance are -1.96 & 1.96}
P(-1.96 < [tex]\frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] < 1.96) = 0.95
P( [tex]-1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] < [tex]{\hat p-p}[/tex] < [tex]1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] ) = 0.95
P( [tex]\hat p-1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] < p < [tex]\hat p+1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] ) = 0.95
95% confidence interval for p = [[tex]\hat p-1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex] , [tex]\hat p+1.96 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }[/tex]]
= [ [tex]0.125-1.96 \times {\sqrt{\frac{0.125(1-0.125)}{270} } }[/tex] , [tex]0.125+1.96 \times {\sqrt{\frac{0.125(1-0.125)}{270} } }[/tex] ]
= [0.08 , 0.16]
Therefore, 95% confidence interval for the population proportion who use cell phones primarily for e-mail is [0.08 , 0.16].
Since, the above confidence interval have values which is less than 0.17; so we conclude that the population proportion is less than 0.17.