Back in 1903, a few years after the discovery of X-rays by German researchers, a French scientist named René Blondlot announced that he'd discovered yet another previously unknown form of radiation — N-rays. They could only be observed using peripheral vision, and seen as a corona when electricity was discharged from crystals. Eventually, Blondlot's research was refuted by an American scientist, Robert Wood, who visited the Frenchman's lab and found that Blondot still observed N-rays, even after Wood secretly removed the crystal during one of the experiments.
But after that, something strange happened. For years, other French scientists continued to publish papers describing their observations of N-rays, as if they actually existed. Perhaps out of nationalistic pride, French scientists wanted to see N-rays, and so they did [sources: Lee, Simon].
Those N-ray findings were an extreme example of one of the simplest most widely recognized reasons that studies can go wrong — confirmation bias. That's when a researcher takes the hypothesis that he or she starts out with ("marijuana is beneficial/detrimental") and shapes the study methodology or the analysis of the data in a way that confirms the original premise, whether or not it's actually justified [source: Sarniak]. Lay people are prey to confirmation bias as well. If they support (or despise) a sitting president of the U.S., for instance, they tend to look for information that confirms their view and disregard anything that refutes it.