Law of Small Numbers

A cognitive bias and informal heuristic describing the mistaken belief that small samples will reflect the properties of the underlying population as reliably as large samples do; it leads to overinterpretation of patterns, underestimation of sampling variability and premature generalization from limited clinical data.