Commentary is presented on the preceding articles in this issue of the journal. Critical commentary is made article by article, and some general recommendations are made. (See TM 503 664 through 670). (JKS)

Multiple comparisons involve the examination of which group or groups are actually different from other group(s) in analysis of variance results. Such comparisons usually involve one-way analysis of variance. This monograph discusses designs more complex than one-way designs. (JKS)

Issues in analysis of covariance, multiple regression analysis, and the analysis of variance such as the assumption of independence and directional hypotheses are discussed. (JKS)

A data set from the area of clinical psychology was used to show how multiple regression analysis could be used where analysis of variance might more commonly be used. (JKS)

Recent criticism in the literature of the use of inferential statistics in educational research is refuted. The authors focus on the defense of multiple regression analysis. (JKS)

The construction and interpretation of confidence intervals for the prediction of new cases in multiple regression analysis is explained. An example is provided. (JKS)

Problems associated with the use of gain scores, analysis of covariance, multicollinearity, part and partial correlation, and the lack of rectilinearity in regression are discussed. Particular attention is paid to the misuse of statistical techniques. (JKS)

With even the simplest bivariate regression, least-squares solutions are inappropriate unless one assumes a priori that reciprocal effects are absent, or at least implausible. While this discussion is limited to bivariate regression, the issues apply equally to multivariate regression, including stepwise regression. (Author/CTM)