Recently, there has a been a lot of discussion about issues of reproducibility in the biomedical and psychological literature. Some people argue that the threshold for statistical signifance should be lowered, say p = 0.01 instead of 0.05. This paper argues, and in my opinion rightly so, that the use of statistical signifance should be abandoned. One of the main arguments, which I also defended in a blog post, is that the null hypothesis is not credible. When any manipulation on a living being is performed, it is unrealistic to hypothesize that the effect will be exactly 0. It might be small, yes, but not exactly zero. And if it’s not zero, then with a sufficient number of observations there is 100% probability that you find a statistically significant effect, whatever threshold you use. The term “significance” is misleading; a ridiculously small effect would still be statistically significant, provided enough observations. It doesn’t prove much, apart from the fact that you are ready to sacrifice hundreds of animals just to get published by glamour journals. Conversely, finding that something is not significant means literally nothing: it could be that you just haven’t repeated the experiment a sufficient number of times – in fact it must be this interpretation, given that the null hypothesis is not realistic. So, I agree with the authors that statistical significance should be abandoned, in favor of more meaningful statistical measures (for example effect size).