The concept of statistical significance is nonsense. In Bayesian statistics there is only evidence. A p value of 0.05 is roughly equivalent to a factor 20 of ev

The concept of statistical significance is nonsense. In Bayesian statistics there is only evidence. A p value of 0.05 is roughly equivalent to a factor 20 of evidence. That means you multiply the odds you believe in a hypothesis by 20 (or add 13 decibels.) Similarly a p value of 0.005 is roughly equivalent to 200 units of evidence (23 decibels.) But whether some amount of evidence is "significant" or not is entirely dependent on your prior. If you believe something has about a 50:50 chance of being true to start with, then a factor 20 of evidence is quite enough. Now you believe it 20:1 likely to be true. But for something like xkcd's "green jelly beans cause cancer", your prior should be something like 1 to 100,000 or even smaller. After all, there are a lot of possible foods and a lot of possible diseases. Unless you believe a significant number of them are dangerous, your prior for any specific food causing any specific disease must be pretty low. And then even a factor 200 of evidence is nowhere near enough to convince me that green jelly beans cause cancer.