Science depends on statistics to allow us to “know” something. We experiment and show differences and try to show that those differences are not just random, but show some underlying effect.

Sometimes, even statistics are not enough, when enough people in a field are convinced of the current theories — which are theories because they can never be “proved.” An example is the struggle of two scientists who saw the data tell them that ulcers were not caused by what “everyone” knew they were caused by, but rather by a bacteria. Publishing their results was frustrated because the reviewers knew they must be wrong.

Lucky for us they persevered, and eventually on the Nobel Prize.