I'm not very familiar with statistical terms, so sorry if I messed up with some namings.
If I have a data set with names and ages.
Tom 12 Jenny 14 Joe 15 Kate 14
And I have a the following choices of ages: [11, 12, 13, 14, 15, 16]
Let's say I don't know the age of each person, I have a task to calculate the average error in age difference, if I randomly assign an age to a person by choosing one of the ages above.
So let's take an example, I randomly chose an age for each person:
Tom 13 Jenny 16 Joe 11 Kate 13
So for tom I have 1 year in difference from the real age, 2 for Jenny....
So the average error in age difference from the real age would be: (1 + 2 + 4 + 1)/4 = 2
I don't know how to think about it in a more general way. What can I use to get the average error in a large dataset if I chose random ages from a list?
Extra info: The purpose of this task is that, I am creating a machine learning algorithm that predict the age of each person based on other data, and I want to compare the results with the results of a random distribution of age. To see if my prediction gives better results (less average error) than just a random pick
Hope my question made sense.