Small Sample

This is the fallacy of using too small a sample. If the sample is too small to provide a representative sample of the population, and if we have the background information to know that there is this problem with sample size, yet we still accept the generalization upon the sample results, then we commit the fallacy. This fallacy is the fallacy of hasty generalization, but it emphasizes statistical sampling techniques.

Example:

I've eaten in restaurants twice in my life, and both times I've gotten sick. I've learned one thing from these experiences: restaurants make me sick.

How big a sample do you need to avoid the fallacy? Relying on background knowledge about a population's lack of diversity can reduce the sample size needed for the generalization. With a completely homogeneous population, a sample of one is large enough to be representative of the population; if we've seen one electron, we've seen them all. However, eating in one restaurant is not like eating in any restaurant, so far as getting sick is concerned. We cannot place a specific number on sample size below which the fallacy is produced unless we know about homogeneity of the population and the margin of error and the confidence level.