Using the z-distribution, as we are working with a proportion, it is found that the 99% confidence interval for the proportion of all U. S. Adults who would include the 9/11 attacks on their list of 10 historic events is (0.7458, 0.7942). It means that we are 99% sure that the true proportion for all U.S. adults is between these two bounds.
<h3>What is a confidence interval of proportions?</h3>
A confidence interval of proportions is given by:

In which:
is the sample proportion.
In this problem, the parameters are:

The lower limit of this interval is:

The upper limit of this interval is:

The 99% confidence interval for the proportion of all U. S. Adults who would include the 9/11 attacks on their list of 10 historic events is (0.7458, 0.7942). It means that we are 99% sure that the true proportion for all U.S. adults is between these two bounds.
More can be learned about the z-distribution at brainly.com/question/25890103
Answer: the number is 3.
Step-by-step explanation:
(x × 10) + 6 = 36
[(3) × 10] + 6 = 36
Answer:

Step-by-step explanation:

Hope this helps!