Suggested by Pedro.
P values, the ‘gold standard’ of statistical validity, are not as reliable as many scientists assume.
… For many scientists, this is especially worrying in light of the reproducibility concerns. In 2005, epidemiologist John Ioannidis of Stanford University in California suggested that most published findings are false2; since then, a string of high-profile replication problems has forced scientists to rethink how they evaluate results.
At the same time, statisticians are looking for better ways of thinking about data, to help scientists to avoid missing important information or acting on false alarms. “Change your statistical philosophy and all of a sudden different things become important,” says Steven Goodman, a physician and statistician at Stanford. “Then ‘laws’ handed down from God are no longer handed down from God. They’re actually handed down to us by ourselves, through the methodology we adopt.”