Answer:
A sample of
is needed, in which E is the desired margin of error, as a proportion. If we find a decimal value, we round up to the next whole number.
Step-by-step explanation:
In a sample with a number n of people surveyed with a probability of a success of
, and a confidence level of
, we have the following confidence interval of proportions.
![\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}](https://tex.z-dn.net/?f=%5Cpi%20%5Cpm%20z%5Csqrt%7B%5Cfrac%7B%5Cpi%281-%5Cpi%29%7D%7Bn%7D%7D)
In which
z is the zscore that has a pvalue of
.
The margin of error is of:
![M = z\sqrt{\frac{\pi(1-\pi)}{n}}](https://tex.z-dn.net/?f=M%20%3D%20z%5Csqrt%7B%5Cfrac%7B%5Cpi%281-%5Cpi%29%7D%7Bn%7D%7D)
In a previous study of 1012 randomly chosen respondents, 374 said that there should be such a law.
This means that ![n = 1012, \pi = \frac{374}{1012} = 0.3696](https://tex.z-dn.net/?f=n%20%3D%201012%2C%20%5Cpi%20%3D%20%5Cfrac%7B374%7D%7B1012%7D%20%3D%200.3696)
95% confidence level
So
, z is the value of Z that has a pvalue of
, so
.
How large a sample size is needed to be 95% confident with a margin of error of E?
A sample size of n is needed, and n is found when M = E.
![M = z\sqrt{\frac{\pi(1-\pi)}{n}}](https://tex.z-dn.net/?f=M%20%3D%20z%5Csqrt%7B%5Cfrac%7B%5Cpi%281-%5Cpi%29%7D%7Bn%7D%7D)
![E = 1.96\sqrt{\frac{0.3696*0.6304}{n}}](https://tex.z-dn.net/?f=E%20%3D%201.96%5Csqrt%7B%5Cfrac%7B0.3696%2A0.6304%7D%7Bn%7D%7D)
![E\sqrt{n} = 1.96\sqrt{0.3696*0.6304}](https://tex.z-dn.net/?f=E%5Csqrt%7Bn%7D%20%3D%201.96%5Csqrt%7B0.3696%2A0.6304%7D)
![\sqrt{n} = \frac{1.96\sqrt{0.3696*0.6304}}{E}](https://tex.z-dn.net/?f=%5Csqrt%7Bn%7D%20%3D%20%5Cfrac%7B1.96%5Csqrt%7B0.3696%2A0.6304%7D%7D%7BE%7D)
![(\sqrt{n})^2 = (\frac{1.96\sqrt{0.3696*0.6304}}{E})^2](https://tex.z-dn.net/?f=%28%5Csqrt%7Bn%7D%29%5E2%20%3D%20%28%5Cfrac%7B1.96%5Csqrt%7B0.3696%2A0.6304%7D%7D%7BE%7D%29%5E2)
![n = (\frac{1.96\sqrt{0.3696*0.6304}}{E})^2](https://tex.z-dn.net/?f=n%20%3D%20%28%5Cfrac%7B1.96%5Csqrt%7B0.3696%2A0.6304%7D%7D%7BE%7D%29%5E2)
A sample of
is needed, in which E is the desired margin of error, as a proportion. If we find a decimal value, we round up to the next whole number.