Moreover, since the strength of statistical inferences depend upon the similarity of the sample and population, they are really a species of argument from analogy , and the strength of the inference varies directly with the strength of the analogy. Thus, a statistical inference will commit the Fallacy of Unrepresentative Sample when the similarity between the sample and population is too weak to support the conclusion. The sample is simply too small to represent the population, in which case the argument will commit the subfallacy of Hasty Generalization . The sample is biased in some way as a result of not having been chosen randomly from the population. The Example is a famous case of such bias in a sample.
Small samples can be representative, and even a sample of one is sufficient in some cases.