Everyone knows that "good things come in small packages." But in research evaluating practical educational programs, this saying does not apply. Small studies are very susceptible to bias. In fact, among all the factors that can inflate effect sizes in educational experiments, small sample size is among the most powerful. This problem is widely known, and in reviewing large and small studies, most meta-analysts solve the problem by requiring minimum sample sizes and/or weighting effect sizes by their sample sizes. Problem solved.