> just doing statistics on a set of data can't tell you "the truth". If you don't understand the actual causal factors in play, your knowledge is very limited
I would argue that ultimately, all your knowledge and understanding comes from "doing statistics on data". Maybe the statistics is done by sloppy slurpy things in the brain instead of in R, and maybe it's actually mathematically unsound most of the time, but it's still some sort of statistics.
I think the key difference is between statistics on passively collected data vs results from active experiments. The former will only ever show correlations, while the latter can prove causal results from the actions of the experimenter.
Also, results from active experiments aren't limited to statistics. You can set up experiments to have discrete results, where no statistics is required to test a hypothesis.
For example, the GHZ experiment [1] can rule out local hidden variable models and confirm QM predictions with no statistics at all: the two different models make contradictory predictions with no continuous variation between them.
Sure, but that doesn't contradict what I said. From the Wikipedia article I referenced:
"For specific combinations of orientations, perfect (rather than statistical) correlations between the three polarizations are predicted by both local hidden variable theory (aka "local realism") and by quantum mechanical theory, and the predictions may be contradictory."
"Perfect" correlations means, as the parenthetical comment shows, "doesn't require statistics to check".
> the GHZ experiment [1] can rule out local hidden variable models and confirm QM predictions with no statistics at all
However, one needs to use statistics to even show GHZ works. That does sound contradictory to me. The correlations you get in experiments are never perfect and in this case they can be pretty far from perfect.
> one needs to use statistics to even show GHZ works
Not for the particular cases described in the quote I gave. For a complete verification of all the GHZ theorem's predictions, yes, you need to do statistics, because some of those predictions are probabilistic.
> The correlations you get in experiments are never perfect
In some cases, like the ones described in the quote I gave, it isn't a matter of correlations. You have contradictory results predicted by two different models, each prediction being 100% certain according to the model. You don't need any statistics to test that: just do one single run and see which way it comes out.
I would argue that ultimately, all your knowledge and understanding comes from "doing statistics on data". Maybe the statistics is done by sloppy slurpy things in the brain instead of in R, and maybe it's actually mathematically unsound most of the time, but it's still some sort of statistics.