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. (Links to an external site.) 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? (Links to an external site.) Comic: Significant (XKCD) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/ https://amstat.tandfonline.com/doi/full/10.1080/00031305.2016.1154108#.XsGbSURKiUk https://www.youtube.com/watch?v=42QuXLucH3Q https://xkcd.com/882/