When working with numbers representing many people, one often employs the average to describe the people represented by the numbers. However, this approach can lead to serious problems due to the flaw of averages, which is that findings based on the average are wrong on average.
In fact, often when dealing with people, the average person does not exist!
The average applies to a collection, group, population, segment, sample, etc., yet is nearly meaningless at the individual level and hides what is usually a distribution. The flaw of averages is wrong in most contexts but nearly always wrong when dealing with many types of online people data. This is because many, but naturally not all, methods relying on the average assume a normal distribution, whereas much of the online people data follows a power law distribution. In power law distributions, the data is so skewed that a large percentage of the population would deviate from any ‘average’.
The flaw of averages is a data analysis problem – the average person does not exist.
For more on the flaw of averages, see:
Jansen, B. J., Salminen, J., Jung, S.G., and Almerekhi, H. (2022) The Illusion of Data Validity: Why Numbers About People Are Likely Wrong. Data and Information Management.