Medical scientists study the effect of acute infection on tissue-specific immunity. In a collection of experiments under the same conditions, 44 of 75 mice test positive for lymphadenopathy. Compute a 95% confidence interval for the true proportion of mice that will test positive under similar conditions.

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Answer:

The 95% confidence interval  for the true proportion of mice that will test positive under similar conditions is (0.5291, 0.6429).

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 interval [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].

For this problem, we have that:

In a collection of experiments under the same conditions, 44 of 75 mice test positive for lymphadenopathy. This means that [tex]n = 75[/tex] and [tex]\pi = \frac{44}{75} = 0.586[/tex].

Compute a 95% confidence interval for the true proportion of mice that will test positive under similar conditions.

So [tex]\alpha = 0.05[/tex], z is the value of Z that has a pvalue of [tex]1 - \frac{0.05}{2} = 0.975[/tex], so [tex]Z = 1.96[/tex].

The lower limit of this interval is:

[tex]\pi - z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.586 - 1.96\sqrt{\frac{0.586*0.414}{75}} = 0.5291[/tex]

The upper limit of this interval is:

[tex]\pi - z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.586 + 1.96\sqrt{\frac{0.586*0.414}{75}} = 0.6429[/tex]

The 95% confidence interval  for the true proportion of mice that will test positive under similar conditions is (0.5291, 0.6429).

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