Respuesta :
Answer:
[tex] ME= t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]
No matter the confidence level used we can express the margin of error like this:
[tex] ME = t \frac{10.19}{\sqrt{30}}= 1.8604 t[/tex]
And if we want to reduce this margin of error to the half we need a new margin of error of [tex] ME= 0.9302 t[/tex]
And using the formula for the margin of error we have:
[tex] 0.9302 t = t \frac{10.19}{\sqrt{n}}[/tex]
And solving for n we got:
[tex] n = (\frac{10.19}{0.9302})^2 = 120[/tex]
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
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".
[tex]\bar X=29.61[/tex] represent the sample mean for the sample
[tex]\mu[/tex] population mean (variable of interest)
s=10.19 represent the sample standard deviation
n=30 represent the original sample size
The confidence interval for the mean is given by the following formula:
[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex] (1)
Solution to the problem
For this case the margin of error is given by:
[tex] ME= t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]
No matter the confidence level used we can express the margin of error like this:
[tex] ME = t \frac{10.19}{\sqrt{30}}= 1.8604 t[/tex]
And if we want to reduce this margin of error to the half we need a new margin of error of [tex] ME= 0.9302 t[/tex]
And using the formula for the margin of error we have:
[tex] 0.9302 t = t \frac{10.19}{\sqrt{n}}[/tex]
And solving for n we got:
[tex] n = (\frac{10.19}{0.9302})^2 = 120[/tex]