To add to this, the main problem with null hypothesis testing IMO is that mathematically you are comparing a infinitesimally small hypothesis: effect exactly equals 0.000000000000... to an infinitely large one: effect is somewhere between 0.00000...00001 and infinity.
A tiny effect is very easy to reject (p<0.0000...000001). I can tell you before running the experiment that any two objects close enough for long enough to be in each other's light cone have at least a tiny effect on each other.
The null hypothesis is hereby rejected for most anything relevant to humans. No need to calculate p-values. Just reference this comment.
A tiny effect is very easy to reject (p<0.0000...000001). I can tell you before running the experiment that any two objects close enough for long enough to be in each other's light cone have at least a tiny effect on each other.
The null hypothesis is hereby rejected for most anything relevant to humans. No need to calculate p-values. Just reference this comment.