> and after the fact you discovered a class of patients responded differently than the rest and you could find a good classifier, then it's certainly not fraud

> and after the fact you discovered a class of patients responded differently than the rest and you could find a good classifier, then it's certainly not fraud Or you could say "after the fact you chose/created the class of patients that responded differently". It certainly is fraudulent, I suppose this issue isn't quite a Stats 101 thing, but it's certainly undergrad level because it's only a little bit subtle. A useful metaphor to keep in mind is the one that gives the Texas Sharpshooter Fallacy it's name: "The name comes from a joke about a Texan who fires some shots at the side of a barn, then paints a target centered on the biggest cluster of hits and claims to be a sharpshooter." The examples on wikipedia are also instructive (http://en.wikipedia.org/wiki/Texas_sharpshooter_fallacy http://en.wikipedia.org/wiki/Texas_sharpshooter_fallacy) As PeterisP pointed out, the only correct interpretation is to say "That's interesting, we need to do another study with that subgroup to see if that's a real effect" (although that xkcd comic illustrates what's called "The Filedrawer Effect" or simply "publication bias" which is the same error made a different way). Give me a dataset of people rolling dice many times and the ability to group them after examining the data and I will find you a group that seems to have magical craps playing abilities that don't actually exist. It might be men over 6' with brown hair or it might be married people who are left handed or maybe bilingual introverts ... who knows, I can't tell you what that group will be until I see the data (and that last statement is why you know it's not a real ability). This is precisely why experimental design depends on defining your tests before you examine your data or, put another way, you cannot use the data that suggested an effect to prove an effect. The idea that the CEO of a biotech company didn't know this is absurd, because this is Running a Scientific Experiment 101. Selecting groups after seeing the data is probably the most common method chosen to tweak failed experiments by those committing fraud, second is probably using the filedrawer (just rerun the experiment until you get a result by chance and pretend the failed experiments never happened). These are so rife that there are hundreds of articles about the prevalence of this type of fraud published in the last few years. This type of behaviour is a big deal these days.