The idea of misinterpreting metrics is a very general idea and is not specific to statistics.
Humans want to distill vast amounts of information to a more manageable amount, like for example a single number.
Equity analysts look at accounting metrics, psychologists look at psychometrics test cores, doctors look at some function of blood pressure, etc etc.
Any person with deductive and sceptical mental faculties in place, will recognize that these are all simplifications, and cannot be used to deliver a unified truth.
Also, being aware of this has very little to do with being technical or not (for example, plenty of programmers only look at a CPU's clock speed to gauge performance).
Humans want to distill vast amounts of information to a more manageable amount, like for example a single number.
Equity analysts look at accounting metrics, psychologists look at psychometrics test cores, doctors look at some function of blood pressure, etc etc.
Any person with deductive and sceptical mental faculties in place, will recognize that these are all simplifications, and cannot be used to deliver a unified truth.
Also, being aware of this has very little to do with being technical or not (for example, plenty of programmers only look at a CPU's clock speed to gauge performance).
Anyhow, nice post.