pp. Manipulating scientific data so that the results appear to be statistically significant.
Other Forms
If we’re going to rely on science as a means for reaching the truth — and it’s still the best tool we have — it’s important that we understand and respect just how difficult it is to get a rigorous result. I could pontificate about all the reasons why science is arduous, but instead I’m going to let you experience one of them for yourself. Welcome to the wild world of p-hacking.
—Christie Aschwanden, “Science Isn't Broken,” FiveThirtyEight, August 19, 2015
Perhaps the worst fallacy is the kind of self-deception for which psychologist Uri Simonsohn of the University of Pennsylvania and his colleagues have popularized the term P-hacking; it is also known as data-dredging, snooping, fishing, significance-chasing and double-dipping.
—Regina Nuzzo, “Scientific method: Statistical errors,” Nature, February 12, 2014
Almost more alarming than the few individuals committing academic fraud are the high percentage of researchers who admitted to more common questionable research practices, like post-hoc theorizing and data-fishing (sometimes referred to as p-hacking), in a recent study led by Leslie John.
—Sarah Estes, “The Myth of Self-Correcting Science,” The Atlantic, December 20, 2012
2012 (earliest)
In the final talk, Uri Simonsohn of UPenn discussed what he refers to as "p-hacking." P-hacking is the idea that if researchers are engaging in questionable analysis practices, then they should have a disproportionate number of findings at or close to the p < .05 threshold for statistical significance, and that this can be relatively easy to detect.
—Michael Kraus, “SPSP 2012: Watchdogs, Witch-hunts, and What to do about False-Positive Findings,” Psych Your Mind, January 27, 2012
In statistics, the P value is the probability that an effect shown by scientific data is not a real effect and is, instead, just an artifact of the methodology (such as a random sampling error). If P is low (the usual threshold is five percent, or 0.05), then the effect shown by the data is said to be statistically significant.
Filed Under