A researcher wishes to estimate the proportion of adults who have​ high-speed Internet access. What size sample should be obtained if she wishes the estimate to be within 0.040.04 with 9999​% confidence if ​(a) she uses a previous estimate of 0.540.54​? ​(b) she does not use any prior​ estimates?

Respuesta :

Answer:

(a) The sample size required is 1034.

(b) The sample size required is 1040.

Step-by-step explanation:

The confidence interval for population proportion is:

[tex]CI=\hat p\pm z_{ \alpha /2}\sqrt{\frac{\hat p(1-\hat p)}{n} }[/tex]

The margin of error is:

[tex]MOE=z_{ \alpha /2}\sqrt{\frac{\hat p(1-\hat p)}{n} }[/tex]

Given:

[tex]MOE= 0.04\\Confidence\ level =0.99[/tex]

The critical value of z for 99% confidence level is:

[tex]z_{\alpha /2}=z_{0.01/2}=z_{0.005}=2.58[/tex] *Use a standard normal table.

(a)

Compute the sample size required if the previous estimate is [tex]\hat p = 0.54\\[/tex] as follows:

[tex]MOE=z_{ \alpha /2}\sqrt{\frac{\hat p(1-\hat p)}{n} }\\0.04=2.58\times \sqrt{\frac{0.54(1-0.54)}{n} }\\n=\frac{(2.58)^{2}\times 0.54\times (1-0.54)}{(0.04)^{2}} \\=1033.4061\\\approx1034[/tex]

Thus, the sample size required is 1034.

(b)

Compute the sample size required if there was no previous estimate as follows:

Assume that the estimated proportion be 0.50.

[tex]MOE=z_{ \alpha /2}\sqrt{\frac{\hat p(1-\hat p)}{n} }\\0.04=2.58\times \sqrt{\frac{0.50(1-0.50)}{n} }\\n=\frac{(2.58)^{2}\times 0.50\times (1-0.50)}{(0.04)^{2}} \\=1040.0625\\\approx1040[/tex]

Thus, the sample size required is 1040.