You want to obtain a sample to estimate a population proportion. Based on previous evidence, you believethe population proportion is approximately 19%. You would like to be 99% confident that your estimate is within 1.5% of the true population proportion. How large of a sample size is required? Do not round mid-calculation.n

Respuesta :

We are given

Proportion (p)

[tex]p=19\%=0.19[/tex]

Level of significance = 99%

margin of error = 1.5% = 0.015

We want to find n

Solution

Note: The margin of error formula is given as

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

The image of the formula to use is

In the question, we have

[tex]\begin{gathered} \alpha=0.01 \\ \text{from the statistics table} \\ z_{\frac{\alpha}{2}}=z_{\frac{0.01}{2}}=z_{0.005}=2.576 \end{gathered}[/tex][tex]\begin{gathered} p=0.19 \\ MarginOfError=0.015 \end{gathered}[/tex]

Substituting the parameters

[tex]\begin{gathered} MarginOfError=z_{\frac{\alpha}{2}}\times\sqrt[]{\frac{p(1-p)}{n}} \\ 0.015=2.576\times\sqrt[]{\frac{0.19(1-0.19)}{n}} \\ \sqrt[]{\frac{0.19(1-0.19)}{n}}=\frac{0.015}{2.576} \\ \frac{0.19(0.81)}{n}=(\frac{15}{2576})^2 \\ \frac{n}{0.19(0.81)}=(\frac{2576}{15})^2 \\ n=0.19(0.81)(\frac{2576}{15})^2 \\ n=4538.870784 \\ n=4539\text{ (to the nearest whole number)} \end{gathered}[/tex]

Therefore, the sample size is as large as

[tex]n=4539[/tex]

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