p-hacking is innocently or deliberating manipulating research to get a statistically significant p-value. In this way researchers can get published, but this also creates a high percentage of false studies. As we learned in class, the p-value is the conditional probability of getting data at least as extreme as what was observed GIVEN the Null Hypothesis is true. Many people incorrectly interpret a low p-value to mean there is a high probability that the claim they desire to publish (the Alternative Hypothesis) is true. Sometimes, researchers will test for many effects and only publish results that have a statistically significant p-value < 0.05. This is considered bad scientific methodology and is given the name data dredging or p-hacking. In 2005 a paper was published John P. A. Ioannidis, “Why Most Published Research Findings Are False” (Links to an external site.) shook the scientific world, bring to light the problem of p-hacking. Still p-hacking has continued unabated and in 2016 a social science journal stopped accepting research using the p-value. The American Statistical Association then published it’s first ever Statement on properly interpreting p-values.
For this week, watch the video and then view the XKCD comic below on p-hacking.
Share whatever you want on what you learned.
Video: Is Most Published Research Wrong?
Comic: Significant (XKCD)
https://xkcd.com/882/For more information on P Hacking check out : https://en.wikipedia.org/wiki/Data_dredging
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