Answer:
A sample size of 6755 or higher would be appropriate.
Step-by-step explanation:
In a sample with a number n of people surveyed with a probability of a success of [tex]\pi[/tex], and a confidence level of [tex]1-\alpha[/tex], we have the following confidence interval of proportions.
[tex]\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]
In which
z is the zscore that has a pvalue of [tex]1 - \frac{\alpha}{2}[/tex].
The margin of error M is given by:
[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]
90% confidence level
So [tex]\alpha = 0.1[/tex], z is the value of Z that has a pvalue of [tex]1 - \frac{0.1}{2} = 0.95[/tex], so [tex]Z = 1.645[/tex].
52% of Independents in the sample opposed the public option.
This means that [tex]p = 0.52[/tex]
If we wanted to estimate this number to within 1% with 90% confidence, what would be an appropriate sample size?
Sample size of size n or higher when [tex]M = 0.01[/tex]. So
[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]
[tex]0.01 = 1.645\sqrt{\frac{0.52*0.48}{n}}[/tex]
[tex]0.01\sqrt{n} = 0.8218[/tex]
[tex]\sqrt{n} = \frac{0.8218}{0.01}[/tex]
[tex]\sqrt{n} = 82.18[/tex]
[tex]\sqrt{n}^{2} = (82.18)^{2}[/tex]
[tex]n = 6754.2[/tex]
A sample size of 6755 or higher would be appropriate.