An engineer for an electric fencing company is interested in the mean length of wires being cut automatically by machine. The desired length of the wires is 12 feet. It is known that the standard deviation in the cutting length is 0.15 feet. Suppose the engineer decided to estimate the mean length to within 0.025 with 99% confidence. What sample size would be needed?

Respuesta :

Answer:

[tex]n=(\frac{2.58(0.15)}{0.025})^2 =239.63 \approx 240[/tex]

So the answer for this case would be n=240 rounded up to the nearest integer

Step-by-step explanation:

We know the following info:

[tex]\sigma =0.15[/tex] represent the population deviation

[tex] ME= 0.025[/tex] the margin of error desired

The margin of error is given by this formula:

[tex] ME=z_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]    (a)

And on this case we have that ME =0.025 and we are interested in order to find the value of n, if we solve n from equation (a) we got:

[tex]n=(\frac{z_{\alpha/2} s}{ME})^2[/tex]   (b)

The critical value for 99% of confidence interval now can be founded using the normal distribution. And we got [tex]z_{\alpha/2}=2.58[/tex], replacing into formula (b) we got:

[tex]n=(\frac{2.58(0.15)}{0.025})^2 =239.63 \approx 240[/tex]

So the answer for this case would be n=240 rounded up to the nearest integer