The average of a data set, formally called the mean, expresses the typical value in that data set. It is calculated by adding up all of the values, and dividing the sum by the size of the data set. For example, four friends take a quiz. Alice and Bob each get 3 questions right, Carol gets 4 right, and Dan gets 5 right. To calculate the mean, do the following:

sum  = 3 + 3 + 4 + 5 = 15
size = 4
mean = 15 ÷ 4 = 3.75

In the example above, 3.75 expresses the typical quiz score. Note that none of the friends actually scored a 3.75, which is not even possible since a quiz score must be a whole number. The mean represents how people scored on the quiz overall.

Now let's say you want to get a general idea of how much money a group of friends have. Alice and Bob each have a net worth of $150,000, Carol is worth $75,000, Dan is worth $125,000, and Warren is worth $60 million. The mean is $12.1 million, but that implies that each friend is very wealthy, when really most of them have a modest net worth while one is extremely wealthy. For data sets that have extreme outliers, it is better to calculate the median, which is the central value in that data set. It is calculated by sorting the values, and taking the middle value:

sorted = $75K, $125K, $150K, $150K, $60M
median = $150K

In the example above, $150,000 is the central value, which is a better representation of how much money the group of friends have. Even if Warren was worth $600 million, the median would remain the same. The median is not skewed by extreme outliers.