This study investigated how population parameters representing heterogeneity of variance, skewness, kurtosis, bimodality, and outlier-proneness, drawn from normal and eleven non-normal distributions, also characterized the ranks corresponding to independent samples of scores. When the parameters of population distributions from which samples were…

Uses computer simulation to study the effects on parametric and nonparametric statistical tests when assumptions of normality and homogeneity of variance are violated. Results reveal that nonparametric methods are not always acceptable substitutes for parametric methods in research studies when parametric assumptions are not satisfied. (SLD)

The power functions of Student t tests performed on initial scores, ordinary ranks, 3 kinds of modular ranks, and dichotomies were investigated for 1 normal and 3 nonnormal distributions using 2 samples of 26 simulated scores each. Advantages of extending the rank transformation concept are discussed. (SLD)

It is argued that outlier-prone distributions reduce the power of nonparametric tests, but power can be restored through procedures usually associated with parametric tests. Computer simulation is used to show how an outlier detection and downweighting procedure augments the power of the t-test and the Wilcoxon-Mann-Whitney test. (SLD)

It is well known that the two-sample Student t test fails to maintain its significance level when the variances of treatment groups are unequal, and, at the same time, sample sizes are unequal. However, introductory textbooks in psychology and education often maintain that the test is robust to variance heterogeneity when sample sizes are equal.…

A computer simulation compared significance tests of correlation coefficients calculated from initial scores, from ranks assigned by the Spearman method, and from three kinds of modified ranks. Implications of findings for the idea that rank correlation is a nonparametric correlation method are discussed. (SLD)

A modified "F" test is derived that includes a correction for nonindependence of between-groups and within-groups sample values in analysis of variance (ANOVA) designs. Computer simulations based on normal and nonnormal distributions illustrate the usefulness of the approach, which was more powerful than conventional within-subjects…

A program obtained random samples from known populations, some of which violated the homogeneity assumption. Student t tests and Mann-Whitney U Tests were performed on the sample value. Where the t test led to incorrect decisions, the use of Mann-Whitney U test in its place led to poorer results. (JAZ)