P-hacking, also called data dredging, is the practice of running many statistical tests on one dataset and reporting only the ones that come out significant. At a 5% threshold, about 5% of random hypotheses will look significant by chance alone, so a large enough search almost always finds spurious correlations. The term was coined in a 2014 paper by the three researchers behind the Data Colada blog, who were uncovering such problems in social science. It is an example of ignoring the multiple comparisons problem: subgroups are compared without disclosing how many comparisons were run. Done unknowingly or deliberately, it can make false findings appear credible and undermine scientific integrity.

In 1909 D. W. Griffith made a 14-minute film about a speculator who corners the wheat market and doubles the price of bread. A farmer sows his field while a 'Wheat King' gambles in the Chicago wheat pit; bakers raise the loaf from five cents to ten and the poor line up for bread. Griffith cut back and forth between the farm, the feast and the breadline, a technique called parallel editing, so audiences saw both ends of the economy at once. The film drew on Frank Norris's stories and on a real scheme: months earlier Chicago financier James Patten had cornered wheat, sent bread prices up and made about $5 million, roughly $185 million today.