Hasty Generalization
Sometimes, then, it is difficult to decide how many instances are needed to give reasonable support to inductive generalizations; yet many times it is obvious, without going into technical details, that the sample is too small. Drawing an inductive conclusion from a sample that is too small can lead to the fallacy of hasty generalization. It is surprising how common this fallacy is. We see a person two or three times and find him cheerful, and we immediately leap to the conclusion that he is a cheerful person. That is, from a few instances of cheerful behavior, we draw a general conclusion about his personality. When we meet him later and find him sad, morose, or grouchy, we then conclude that he has changed—thus swapping one hasty generalization for another.
This tendency toward hasty generalization was discussed over 200 years ago by the philosopher David Hume, who saw that we have a strong ten- dency to “follow general rules which we rashly form to ourselves, and which are the source of what we properly call prejudice.“1 More recently, this tendency toward hasty generalization has been the subject of extensive psychological investigation. The cognitive psychologists Amos Tversky and Daniel Kahneman put the matter this way: We submit that people view a sample randomly drawn from a population as highly representative, that is, similar to the population in all essential characteristics. Consequently, they expect any two samples drawn from a particular population to be more similar to one another and to the population than sampling theory predicts, at least for small samples
