The tyranny of the p: when significance misleads

Abstract

The p-value has long served as the standard of scientific significance, but its widespread misuse and misunderstanding continue to distort how we interpret data and publish findings. In this Comment, we take a critical look at the scientific overreliance on p-values in quantitative research. Through two illustrative case studies, we showcase how statistical significance can both deceive and obscure, depending on how models are specified and results interpreted. We highlight common misconceptions and argue for a shift in both statistical education and publication norms. This is not a call to abandon the p-value, but a call to reframe it as one small piece in an extended conversation about evidence, uncertainty, and meaning.