A reproductive clinic had a success rate of 25% of patients with live births in 2008. They want to update their success rate (the proportion of live births) for 2020. If they want their estimate to be within 2.5%, how many patient's results should they sample if they plan to use a 99% confidence interval? Round your answer up to the nearest integer.

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Answer:

They should sample the results of 1990 patient results.

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 z-score that has a p-value of [tex]1 - \frac{\alpha}{2}[/tex].

The margin of error is of:

[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

A reproductive clinic had a success rate of 25% of patients with live births in 2008.

This means that [tex]\pi = 0.25[/tex]

99% confidence level

So [tex]\alpha = 0.01[/tex], z is the value of Z that has a p-value of [tex]1 - \frac{0.01}{2} = 0.995[/tex], so [tex]Z = 2.575[/tex].

If they want their estimate to be within 2.5%, how many patient's results should they sample if they plan to use a 99% confidence interval?

They should sample n patients.

n is found for [tex]M = 0.025[/tex]. So

[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

[tex]0.025 = 2.575\sqrt{\frac{0.25*0.75}{n}}[/tex]

[tex]0.025\sqrt{n} = 2.575\sqrt{0.25*0.75}[/tex]

[tex]\sqrt{n} = \frac{2.575\sqrt{0.25*0.75}}{0.025}[/tex]

[tex](\sqrt{n})^2 = (\frac{2.575\sqrt{0.25*0.75}}{0.025})^2[/tex]

[tex]n = 1989.2[/tex]

Rounding up:

They should sample the results of 1990 patient results.

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