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).