Many univariate statistical methods, such as the analysis of variance, t-test, and regression, assume that the dependent variable data have a univariate normal distribution (Hinkle, Weirsma, and Jurs, 1998). Various other statistical methods assume that the error scores are normally distributed (Thompson, 1992). Violating this assumption can be particularly problematic when examining statistical significance (R. Henson, 1999). Because countless people use the normal distribution in their daily lives to understand data ranging from advertisements to research articles, understanding the normal distribution is extremely important. A normal or nonnormal distribution cannot be determined simply by looking at the curve. To determine a distributions normality, one must analyze the data statistically. (Author/SLD)