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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