Answer:
The sample size required is [tex]n = (\frac{1.96*6.84}{M})^2[/tex], in which M is the desired margin of error. If n is a decimal number, it is rounded up to the next integer.
Step-by-step explanation:
We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:
[tex]\alpha = \frac{1 - 0.95}{2} = 0.025[/tex]
Now, we have to find z in the Z-table as such z has a p-value of [tex]1 - \alpha[/tex].
That is z with a pvalue of [tex]1 - 0.025 = 0.975[/tex], so Z = 1.96.
Now, find the margin of error M as such
[tex]M = z\frac{\sigma}{\sqrt{n}}[/tex]
In which [tex]\sigma[/tex] is the standard deviation of the population and n is the size of the sample.
Use 6.84 days as a planning value for the population standard deviation.
This means that [tex]\sigma = 6.84[/tex].
What sample size would be required to obtain a margin of error of M days?
This is n for the given value of M. So
[tex]M = z\frac{\sigma}{\sqrt{n}}[/tex]
[tex]M = 1.96\frac{6.84}{\sqrt{n}}[/tex]
[tex]M\sqrt{n} = 1.96*6.84[/tex]
[tex]\sqrt{n} = \frac{1.96*6.84}{M}[/tex]
[tex](\sqrt{n})^2 = (\frac{1.96*6.84}{M})^2[/tex]
[tex]n = (\frac{1.96*6.84}{M})^2[/tex]
The sample size required is [tex]n = (\frac{1.96*6.84}{M})^2[/tex], in which M is the desired margin of error. If n is a decimal number, it is rounded up to the next integer.