Answer:
n=126
Step-by-step explanation:
Data given and previous concepts
[tex]\bar X=60[/tex] represent the sample mean
[tex]s=11[/tex] represent the sample deviation
n=32 represent the sample size
Confidence =0.95 or 95%
[tex]\alpha =1-0.95=0.05[/tex] represent the significance level
ME= 2 represent the margin of error required
The margin of error is the range of values below and above the sample statistic in a confidence interval.
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".
Assuming the X follows a normal distribution
[tex]X \sim N(\mu, \sigma)[/tex]
Solution to the problem
Since we don't have the population deviation. We know that the margin of error for a confidence interval is given by:
[tex]Me=t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex] (1)
The next step would be find the value of [tex]\t_{\alpha/2}[/tex], [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2=0.025[/tex]. The degrees of freedom are given by:
[tex]df=n-1=32-1=31[/tex]
Using the normal standard table, excel or a calculator we see that:
[tex]t_{\alpha/2}=2.04[/tex]
And the code in excel is this one: "=T.INV(1-0.025,31)"
If we solve for n from formula (1) we got:
[tex]\sqrt{n}=\frac{t_{\alpha/2} s}{Me}[/tex]
[tex]n=(\frac{t_{\alpha/2} s}{Me})^2[/tex]
And we have everything to replace into the formula:
[tex]n=(\frac{2.04(11)}{2})^2 =125.88[/tex]
And if we round up the answer we see that the value of n to ensure the margin of error required [tex]\pm=2 miles[/tex] is n=126.