Reexamines David Zarefsky's suggestion that the model of scientific hypothesis testing may offer a new debate paradigm. (PD)

Defends hypothesis testing in academic debate. (PD)

Argues that the practical outcomes of hypothesis testing in academic debate should be considered. (PD)

A general analysis strategy is proposed such that the universe of inference is increased incrementally. The strategy prevents logically incongruent findings that occasionally result when the conventional analysis strategy is employed. (Author)

When homogeneity of slopes is not present, the Johnson-Neyman technique has been considered as an alternative to analysis of covariance. This paper describes how to apply the Johnson-Neyman technique for one or two covariates using the Statistical Package for the Social Sciences (SPSS) or BMDP (Biomedical Computer Programs). (Author/BW)

A concise table is presented based on a general measure of magnitude of effect which allows direct determinations of statistical power over a practical range of values and alpha levels. The table also facilitates the setting of the research sample size needed to provide a given degree of power. (Author/CM)

A solution to some problems of maximized contrasts for analysis of variance situations when the cell sizes are unequal is offered. It is demonstrated that a contrast is maximized relative to the analysis used to compute the sum of squares between groups. Interpreting a maximum contrast is discussed. (Author/GK)

Kahneman and Tversky's critique of Cohen's position on adults' probability reasoning is not valid. If they think Baconian logic is normatively unsound, the onus is on them to explain why. It is valid and useful because nature itself is full of causal processes. (Author/RD)

This article builds on an earlier discussion of the importance of the Type II error (beta) and power to the hypothesis testing process (CE 511 484), and illustrates the methods by which sample size calculations should be employed so as to improve the research process. (Author/CT)

A commentary is made on a previously published article concerning testing the equivalence of covariance matrices. An error in the previous article (by the same authors) is pointed out and the consequences of the error are discussed. (JKS)