I recently read this odd critique of statistics (the author calls it a critique of probability theory, but I think he doesn't understand the difference probability theory and statistics).
In this question, I'm concerned with this specific critique (I already asked another question about the remaining ones):
by hiding the causal factors of an event behind the abstraction of a “probability distribution” we deprive ourselves of the ability to identify when those causal factors change and our assumptions no longer hold (i.e. the distribution shifts). [..] For example, I may experiment with a coin and decide that it is fair when tossing it onto a wooden surface, only to discover later that the coin is magnetized and slightly biased towards heads on metallic surfaces
Isn't this backwards? Actually, statistics allowed us to understand a great deal about a physical system, without having to know the precise laws which determine the behavior of the system, similar to what happens in statistical mechanics. What am I missing here?