The questionable practice of running a large number of statistical tests on a dataset until a statistically significant result occurs. The more statistical tests researchers run, the greater their chance of finding a statistically significant result.
A measure of statistical significance, indicating the probability that the measured outcome would have occurred at random when there was actually no effect. In many fields, p <.05 indicates that a finding is statistically significant.
The process of subjecting a scientific paper to examination by a panel of experts in that field. The peer-review process is foundational to vetting research quality.
The relative difference between two percents. Percent change = (percentage point difference / starting value) x 100.
The difference between two percents when you subtract them. For example, if a flu outbreak infects 3 percent of the population one year and 5 percent the next, that’s a 2-point increase.
An inactive version of the treatment being tested in a study. This will sometimes be given to the control group.
An unpublished manuscript shared online by a researcher. Importantly, preprints haven't undergone peer review.
Often the senior scientist in charge of the lab and the team who ran the study. This person's name is typically listed last in a study's author list.
A belief or claim that's presented as scientific, without being supported by scientific evidence.
Communications staff at an institution who are responsible for liaising with media and providing information to both the press and the public. PIOs can help connect journalists with scientists who have relevant expertise for a story.
The phenomenon in science in which scientists or journals are more likely to publish studies with positive (statistically significant) findings over those with null (not statistically significant) or inconclusive findings.
