fstearns1

Stefan refers to ‘regression to the mean’ as if it were a biological phenomenon. Please refer to page 357 of ‘The Bell Curve’ to disabuse yourself of that notion.

Let's discuss a little more. Suppose you have a scatter graph with the X-axis being the parent's IQ and the Y-axis being the offspring's IQ, and suppose that the correlation is less than 1 and greater than -1. Actually you can use any variables' correlations, not just IQ's. If you choose the parent's IQ as a predictor of offspring's IQ, there will be a regression towards the mean. BUT, if you choose the offspring's IQ as a predictor of the parent's IQ, the parent's IQ will also show a regression to the mean. Again this applies to a static data set, not to generational differences. Let's try a little reductio ad absurdam argument here. If regression to the mean occurs only to the offspring, then selective breeding cannot occur. Clearly this is false. Therefore, the premise is false. I would love to have this discussion directly with Stephan, as I would like to disabuse him of his false understanding of this concept.

Also there is a short summary of the concept in Murray and Herrenstein's "The Bell Curve".

A particularly good explanation of regression to the mean is the YouTube article called "Misunderstanding Regression to the Mean" by Joel Schneider.

You may be confused about the term 'regression'. Regression analysis has nothing to do with 'reversion'. It is a statistical analysis technique concerning a variety of subjects. Again, see the YouTube articles on the subject for enlightenment.

Regression to the mean is a statistical phenomenon, and has nothing to do with generational differences. It simply says that when two variables have a correlation coefficient of less than one, using one variable to predict the value of the other, the other will be closer to to the mean. There are several excellent explanations of this phenomenon on YouTube. It is counterintuitive and almost universally misunderstood.