Taleb has previously undermined the typical interpretation of correlation with regards to the informational value it carries, showing how the uncertainty is reduced in a non-linear fashion.
With regards to a graph showing the relationship between COVID death tolls at lockdown time and the daily deaths afterwards, where the 15% of explained variability ($R^2$) was being used to defend the contribution, he makes the following statement:
an R-squared of .15 means, if you look at it generously, that almost all the variance is for random reasons, something like ~98% (conventional) or (entropy) >99.9%
How can these exact numbers be explained?
Is it related to the sampling distribution of the R^2?
Why is this such an unorthodox interpretation of these statistics?