>"For too long, many scientists’ careers have been built around the pursuit of a single statistic: p<.05."

>"In many scientific disciplines, that’s the threshold beyond which study results can be declared “statistically significant,” which is often interpreted to mean that it’s unlikely the results were a fluke, a result of random chance."

>"Though this isn’t what it actually means in practice. “Statistical significance” is too often misunderstood — and misused. That’s why a trio of scientists writing in Nature this week are calling “for the entire concept of statistical significance to be abandoned.”"

>"Their biggest argument: “Statistically significant” or “not statistically significant” is too often easily misinterpreted to mean either “the study worked” or “the study did not work.” A “true” effect can sometimes yield a p-value of greater than .05. And we know from recent years that science is rife with false-positive studies that achieved values of less than .05 (read my explainer on the replication crisis in social science for more)."

>"The Nature commentary authors argue that the math is not the problem. Instead, it’s human psychology. Bucketing results into “statistically significant” and “statistically non-significant,” they write, leads to a too black-and-white approach to scrutinizing science."

What does /sci/ think about the proposal?

>"In many scientific disciplines, that’s the threshold beyond which study results can be declared “statistically significant,” which is often interpreted to mean that it’s unlikely the results were a fluke, a result of random chance."

>"Though this isn’t what it actually means in practice. “Statistical significance” is too often misunderstood — and misused. That’s why a trio of scientists writing in Nature this week are calling “for the entire concept of statistical significance to be abandoned.”"

>"Their biggest argument: “Statistically significant” or “not statistically significant” is too often easily misinterpreted to mean either “the study worked” or “the study did not work.” A “true” effect can sometimes yield a p-value of greater than .05. And we know from recent years that science is rife with false-positive studies that achieved values of less than .05 (read my explainer on the replication crisis in social science for more)."

>"The Nature commentary authors argue that the math is not the problem. Instead, it’s human psychology. Bucketing results into “statistically significant” and “statistically non-significant,” they write, leads to a too black-and-white approach to scrutinizing science."

What does /sci/ think about the proposal?