Many univariate statistical methods assume that dependent variable data have a univariate distribution. Some statistical methods assume that the error scores are normally distributed. It is clear that the concept of data normality is an important one in statistics. This paper explains that, notwithstanding common misconceptions to the contrary,…

This paper reviews graphical and nongraphical procedures for evaluating multivariate normality by guiding the reader through univariate and bivariate procedures that are necessary, but insufficient, indications of a multivariate normal distribution. A data set using three dependent variables for two groups provided by D. George and P. Mallery…

Nonparametric procedures are often more powerful than classical tests for real world data, which are rarely normally distributed. However, there are difficulties in using these tests. Computational formulas are scattered throughout the literature, and there is a lack of availability of tables of critical values. This paper brings together the…

The effects of skewed theta distributions on indices of differential item functioning (DIF) were studied, comparing Mantel Haenszel (N. Mantel and W. Haenszel, 1959) and DFIT (N. S. Raju, W. J. van der Linden, and P. F. Fleer) (noncompensatory DIF). The significance of the study is that in educational and psychological data, the distributions one…

The advantages that computer adaptive testing offers over linear tests have been well documented. The Computer Adaptive Test (CAT) design is more efficient than the Linear test design as fewer items are needed to estimate an examinee's proficiency to a desired level of precision. In the ideal situation, a CAT will result in examinees answering…