In preparing a report on the​ economy, we need to estimate the percentage of businesses that plan to hire additional employees in the next 60 days. ​a) How many randomly selected employers must we contact in order to create an estimate in which we are 98​% confident with a margin of error of 5​%? ​b) Suppose we want to reduce the margin of error to 3​%. What sample size will​ suffice? ​c) Why might it not be worth the effort to try to get an interval with a margin of error of 1​%?

Respuesta :

Answer:

a) [tex]n=\frac{0.5(1-0.5)}{(\frac{0.05}{2.33})^2}=542.89[/tex]  

And rounded up we have that n=543

b)  [tex]n=\frac{0.5(1-0.5)}{(\frac{0.03}{2.33})^2}=1508.03[/tex]  

And rounded up we have that n=1509

c)  [tex]n=\frac{0.5(1-0.5)}{(\frac{0.01}{2.33})^2}=13572.25[/tex]  

And rounded up we have that n=13573

Step-by-step explanation:

For this case since we don't have previous info we can assume that the best estimator for the true proportion is [tex]\hat p =0.5[/tex]

The margin of error for the proportion interval is given by this formula:  

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

Part a

The significance level is [tex]\alpha=1-0.98 =0.02[/tex]The critical value would be for this case:

[tex]z_{\alpha/2}= 2.33[/tex]

And on this case we have that [tex]ME =\pm 0.05[/tex] and we are interested in order to find the value of n, if we solve n from equation (a) we got:  

[tex]n=\frac{\hat p (1-\hat p)}{(\frac{ME}{z})^2}[/tex]   (b)  

And replacing into equation (b) the values from part a we got:

[tex]n=\frac{0.5(1-0.5)}{(\frac{0.05}{2.33})^2}=542.89[/tex]  

And rounded up we have that n=543

Part b

[tex]n=\frac{0.5(1-0.5)}{(\frac{0.03}{2.33})^2}=1508.03[/tex]  

And rounded up we have that n=1509

Part c

[tex]n=\frac{0.5(1-0.5)}{(\frac{0.01}{2.33})^2}=13572.25[/tex]  

And rounded up we have that n=13573

The randomly selected employee contact in order to create an estimate in which 98​% confident with a margin of error of 5​% is calculated by a margin of error for the proportion interval formula.

(a) 543 randomly selected employers must we contact in order to create an estimate in which we are 98​% confident with a margin of error of 5​%.

(b) The sample size suffice is 1509.

(c) If the margin error is 1% the sample size is 13573.

Given:

Let the best estimator for the true proportion is [tex]\widehat{p}=0.5[/tex].

The significance level is [tex]\alpha=1-098=0.02[/tex].

The critical value would be [tex]z_{\alpha/2}=2.33[/tex]

The margin of error is [tex]ME=\pm0.05[/tex]

(a)

Write the formula of margin of error to find the sample size.

[tex]n=\dfrac{\widehat{p}(1-\widehat{p})}{\left (\dfrac {M.E}{2}\right)^2}[/tex]

Substitute the value.

[tex]n=\dfrac{0.5(1-0.5)}{\left (\dfrac {0.05}{2.33}\right)^2}\\n=542.89[/tex]

(b)

Write the formula of margin of error to find the sample size.

[tex]n=\dfrac{\widehat{p}(1-\widehat{p})}{\left (\dfrac {M.E}{2}\right)^2}[/tex]

Substitute the value.

[tex]n=\dfrac{0.5(1-0.5)}{\left (\dfrac {0.03}{2.33}\right)^2}\\n=1508.3[/tex]

(c)

Write the formula of margin of error to find the sample size.

[tex]n=\dfrac{\widehat{p}(1-\widehat{p})}{\left (\dfrac {M.E}{2}\right)^2}[/tex]

Substitute the value.

[tex]n=\dfrac{0.5(1-0.5)}{\left (\dfrac {0.01}{2.33}\right)^2}\\n=13572.25[/tex]

Thus,

(a) 543 randomly selected employers must we contact in order to create an estimate in which we are 98​% confident with a margin of error of 5​%.

(b) The sample size suffice is 1509.

(c) If the margin error is 1% the sample size is 13573.

Learn more about what margin of error for the proportion interval is here:

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