We can use data from a random sample to make inferences about a population. In this case, our population is all of the visitors of the zoo on Friday, and the random sample is the  visitors that were randomly selected by the owner and asked which exhibit was their favorite.

Based on our answer choices, we are making an inference about which animal exhibit, if the zoo got rid of, would create the most upset visitors. The pandas received the most votes out of the owner's pole; thus, we can infer—based on these results—that if the zoo got rid of the Panda Exhibit, they'd have the most upset visitors. 

The visual overlaps are heights that both dot graphs have in common. In this case, there are both swimmers and basketball players that are , , and ; thus, all the answer choices are correct. 

The mean is the average of a data set. In order to solve for the mean, we add all of our heights together, and divide by the number of people in our data set. 

Basketball players:

Swimmers: 

To find the different, we subtract our two means:

The mean is the average of a data set. In order to solve for the mean, we add all of our heights together, and divide by the number of people in our data set. 

The mean absolute deviation is the average distance between each data point and the mean. So the first step to solving for the mean absolute deviation is to solve for the mean.

The mean is the average of a data set. In order to solve for the mean, we add all of our heights together, and divide by the number of people in our data set. 

Next, we subtract to find the distance between each data point and , which is shown in the following table:

Now that we have all of the distances from the mean, we find the average of those differences to find the mean absolute deviation: 

The median is the middle number of a set of data points. 

To solve for the median, we list our data points in order from least to greatest, and then find the number in the middle. 

There are two numbers in the middle, so we take the average of the two numbers:

The median is the middle number of a set of data points. 

To solve for the median, we list our data points in order from least to greatest, and then find the number in the middle. 

There are two numbers in the middle, so we take the average of the two numbers:

The median is the middle number of a set of data points. 

To solve for the median, we list our data points in order from least to greatest, and then find the number in the middle. 

Swimmers:

There are two numbers in the middle, so we take the average of the two numbers:

Basketball players:

There are two numbers in the middle, so we take the average of the two numbers:

Finally, we subtract to find the difference: 

The mean absolute deviation is the average distance between each data point and the mean. So the first step to solving for the mean absolute deviation is to solve for the mean.

The mean is the average of a data set. In order to solve for the mean, we add all of our heights together, and divide by the number of people in our data set. 

Basketball players:

Next, we subtract to find the distance between each data point and , which is shown in the following table:

Now that we have all of the distances from the mean, we find the average of those differences to find the mean absolute deviation: 

Swimmers:

Next, we subtract to find the distance between each data point and , which is shown in the following table:

Now that we have all of the distances from the mean, we find the average of those differences to find the mean absolute deviation: 

Now that we have each of the mean absolute deviations we can subtract to find the difference:

An outlier is a value in a data set that  lies outside of the rang of the other data points. In this case,  is three inches away from any other height, and there are no other gaps like this in the set; thus,  is our outlier.