[dan_mctree]

It's interesting that high p-values actually seem to more conclusively state something than low p values (like p < 0.05) do.

With a high p value, you can say with some degree of certainty that your test was unable to detect any effect. Whether it was due to the lack of an effect or because your test wasn't capable of measuring it

With a low p value, you don't actually really know if you detected something interesting. It could be due to a flawed test, biases, non-causal correlations, faulty p-hacky stats, etc.

So why do we consider the latter more worthwhile when it seems to say less?