When analysis of variance is used, statistically significant differences may or may not be of practical significance to educators. A large part of the problem is due to the fact that a "zero difference" null hypothesis can always be rejected statistically if the sample size is large enough. If, however, a method based on the noncentral F…

This paper presents an index of goodness-of-fit for comparing m models over n trials. The index allows for differentiated weighting of the trials as to their importance in the comparison of the models. Several possible weighting schemes are suggested and the conditions on the weights which assure asymptotic normality of the index distribution are…

Texts often suggest running preliminary tests for homogeneity of variance prior to running an ANOVA. While it has been known for some time that most of the suggested tests are probably not appropriate, they are still being used. This paper is a review of the literature in terms of the implications involved in running preliminary tests in general…

A statistical method, Fishers Table of t (or t ratio), is used to determine the statistical significance of a comparison of results from pretests and post-tests of knowledge and skill taken by training program participants. A statistically significant improvement can demonstrate training effectiveness. (MS)

Kaufman and Sweet's article on the regression analysis of unbalanced factorial designs (EJ 111 767) is reviewed. A number of errors are noted, and relevant literature is cited. (GDC)

Research hypotheses versus statistical hypotheses, null hypotheses and alternative hypotheses, and statistical significance versus practical significance are described and illustrated. (CP)

The use of measures of magnitude of effect has been advocated as a way to go beyond statistical tests of significance and to identify effects of a practical size. They have been used in meta-analysis to combine results of different studies. Describes problems associated with measures of magnitude of effect (particularly study size) and…

Compares three methods of analyzing pairwise treatment differences in a multi-treatment experiment via computer simulation techniques. Under the equal n condition, the robustness of the conventional Tukey Wholly Significant Difference test (WSD) to heterogeneous variances was contrasted with two alternate techniques. Under unequal n conditions,…

This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…

This tutorial summarizes some of the widely known limitations of tests of statistical significance and then focuses on extracting measures of variation accounted for as a supplement to significance testing. Two measures of variation accounted for, eta squared and omega squared, are discussed. Computational formulas, computational examples, and…

In response to the increasing call by professional organizations, journal editors, and statisticians to include not only derived significance levels from quantitative statistical procedures but also measures of effect sizes (ES), this article first provides a rationale for school counseling-related researchers to include these key indices in their…

Despite the prevalence of multiple choice items in educational testing, there is a dearth of empirical evidence for multiple choice item writing rules. The purpose of this study was to expand the base of empirical evidence by examining the use of the "all-of-the-above" option in a multiple choice examination in order to assess how…

Discusses the necessity for considering significance level reversal when attempting to establish group equivalence prior to treatment. (GS)