The phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement.
Huh? What does that mean?
To understand this, let’s look at Sir Galton’s original study in 1886 - which compared heights of children to their parents. He measured the heights of hundreds of children who’d reached adulthood and the average height of their parents. He was surprised by what he saw when he plotted the data:
It appeared from these experiments that the offspring did not tend to resemble their parents in size, but always to be more mediocre than they – to be smaller than the parents, if the parents were large; to be larger than the parents, if the parents were very small.
Galton originally called this phenomenon “regression towards mediocrity” (if you also have a sense of humor on the dry side this might make you smile - but I digress) - it’s now what’s commonly termed regression to the mean.
🏀 A memorable example: Michael Jordan’s "modestly talented” sons
If you haven’t quite wrapped your head around RTM just yet, just try to remember this (slightly dated but still relevant) example from basketball.
Michael Jordan, the greatest basketball player in the history of the professional game, has two sons who are modest talents at best. The probability that either will make it to a professional league seems low, a reality acknowledged by one of them.
It is still noteworthy of course that both had the talent to make it onto a roster of a Division I NCAA team. This is not typical for any young man walking off the street. But the range in realized talent here is notable.