# Statisticians Found One Thing They Can Agree On: It’s Time To Stop Misusing P-Values

A common misconception among nonstatisticians is that p-values can tell you the probability that a result occurred by chance. This interpretation is dead wrong, but you see it again and again and again and again. The p-value only tells you something about the probability of seeing your results given a particular hypothetical explanation — it cannot tell you the probability that the results are true or whether they’re due to random chance…

Nor can a p-value tell you the size of an effect, the strength of the evidence or the importance of a result. Yet despite all these limitations, p-values are often used as a way to separate true findings from spurious ones, and that creates perverse incentives…

If there’s one takeaway from the ASA statement, it’s that p-values are not badges of truth and $p < 0.05$ is not a line that separates real results from false ones. They’re simply one piece of a puzzle that should be considered in the context of other evidence.

The article above links to the statement by the American Statistical Association as well as various commentaries by statisticians about the proper use of p-values.

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