Abstract

L-shaped distributions are not rare and are probably far more prevalent than is generally realized. They are highly conducive to nonrobustness of normality-assuming statistical tests, and they strongly resist transformation to normality. The thinner the tail of the distribution, the more unlikely it is that its L-shapedness will be detected by inspecting a sample drawn from it. Yet, as the tail of an L-shaped distribution becomes increasingly shallow, its skewness and kurtosis depart increasingly from their “normal-distribution” values, and the distribution becomes increasingly conducive to drastic nonrobustness. Worse, a fairly common type of experimental situation in psychological research produces shallow-tailed L-shaped distributions.