Science should be done with all the "best" words. Data is shown via tweets. Folks with "intelligence" not to be trusted. China is mathematically removed in climate change projections. Hypotheses all end with a "CHA-CHING!" Scientific credentials include showing your birth certificate. "Pussy" is a medically recognized term. Citations include lawsuits. Expert peer review still sound, except for the bit about "expert." All computer stuff to be done by some guy in New Jersey: not Russia. Breibart News is a credible scientific source. Scientific community includes that crazy relative of yours who believes mermaids are real but climate change is not. Impact factor to be replaced with "Is it YUGE?" factor. Bullshit, now the norm.
There has been a lot written over the past decade (and even longer) about problems associated with null hypothesis statistical testing (NHST) and p values. Personally, I have found most of these arguments unconvincing. However, one of the problems with p values has been gnawing at me for the past couple years, and it has finally gotten to the point that I'm thinking about abandoning p values. Note: this has nothing to do with p-hacking (which is a huge but separate issue).
S. Vahdati, N. Arndt, S. Auer, und C. Lange. Proceedings of 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW'2016), 10024, Heidelberg, Springer Verlag, (November 2016)